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paper_name stringlengths 4 421	paper_url stringlengths 21 200	paper_authors listlengths 0 125	paper_abstract stringlengths 0 43.4k	paper_code stringlengths 1 139	conf stringlengths 6 18
42nd IEEE International Conference on Data Engineering, ICDE 2026, Montreal, QC, Canada, May 4-8, 2026	https://doi.org/10.1109/ICDE65706.2026	[]		#	ICDE2026
RISK: Efficiently Processing Rich Spatial-Keyword Queries on Encrypted Geo-Textual Data	https://doi.org/10.1109/ICDE65706.2026.00173	[ "Zhen Lv", "Cong Cao", "Hongwei Huo", "Jiangtao Cui", "Yanguo Peng", "Hui Li", "Yingfan Liu" ]	Symmetric searchable encryption (SSE) for geotextual data has attracted significant attention. However, existing schemes rely on task-specific, incompatible indices for isolated specific secure queries (e.g., range or $\boldsymbol{k}$-nearest neighbor spatial-keyword queries), limiting practicality due to prohibitive m...	#	ICDE2026
RL-Paxos: Relieving the Leader's Burden with Efficient Task Offloading in Distributed Consensus	https://doi.org/10.1109/ICDE65706.2026.00101	[ "Chenhao Zhang", "Jinquan Wang", "Meng Han", "Bing Wei", "Xiaojian Liao", "Limin Xiao", "Shanchen Pang" ]	Existing state machine replication protocols are typically leader-based, with the leader responsible for all operations, leading to a scalability bottleneck. Despite extensive research efforts to address this issue, alleviating the leader's workload remains a significant challenge. In this paper, we provide an indepth ...	#	ICDE2026
Querying Historical $k$-Dense Subgraphs on Temporal Graphs	https://doi.org/10.1109/ICDE65706.2026.00008	[ "Qi Zhang", "Yalong Zhang", "Rong-Hua Li", "Xu-Cheng Yin", "Guoren Wang" ]	Historical cohesive subgraph queries in temporal graphs identify dense substructures within snapshots corresponding to given time intervals, gaining attention due to their broad applications. Existing works primarily focus on $k$-core, which fails to consider subgraph density (measured as the ratio of edges to vertices...	#	ICDE2026
StreamShield: A Production-Proven Resiliency Solution for Apache Flink at Bytedance	https://doi.org/10.1109/ICDE65706.2026.00272	[ "Yong Fang", "Yuxing Han", "Meng Wang", "Yifan Zhang", "Yue Ma", "Chi Zhang" ]	Distributed Stream Processing Systems (DSPSs) form the backbone of real-time processing and analytics at ByteDance, where Apache Flink powers one of the largest production clusters worldwide. Ensuring resiliency, the ability to withstand and rapidly recover from failures, together with operational stability, which prov...	#	ICDE2026
On Graph Rewiring with Motifs: A Find-and-Replace Approach	https://doi.org/10.1109/ICDE65706.2026.00017	[ "Qihao Wang", "Hongtai Cao", "Xiaodong Li", "Matin Najafi", "Kevin Chen-Chuan Chang", "Reynold Cheng" ]	Homophily, which expects that similar nodes should be more likely to be connected, is desired in many graph analytics applications like community detection, node ranking, and node classification. However, real-world graphs may not have high homophily, so some existing works adopt graph rewiring to improve it. Existing ...	#	ICDE2026
AGRAG: Advanced Graph-Based Retrieval-Augmented Generation for LLMs	https://doi.org/10.1109/ICDE65706.2026.00110	[ "Yubo Wang", "Haoyang Li", "Fei Teng", "Lei Chen" ]	Graph-based retrieval-augmented generation (Graph-based RAG) has demonstrated significant potential in enhancing Large Language Models (LLMs) with structured knowledge. However, existing methods face three critical challenges: Inaccurate Graph Construction, caused by LLM hallucination; Poor Reasoning Ability, caused by...	https://github.com/Wyb0627/AGRAG	ICDE2026
Boosting Small Language Models for Text-to-SQL with Fine-Grained Execution Feedback and Cost-Efficient Rewards	https://doi.org/10.1109/ICDE65706.2026.00183	[ "Thanh Dat Hoang", "Thanh Trung Huynh", "Matthias Weidlich", "Thanh Tam Nguyen", "Tong Chen", "Hongzhi Yin", "Quoc Viet Hung Nguyen" ]	Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data privacy concerns, which make them impractical for many real-world applications. A natural alternative is to use small language models (SLMs), which enable efficient and p...	https://github.com/thanhdath/finer-sql	ICDE2026
Improving GPU Tensor Query Processing for Resource-Constrained Environments	https://doi.org/10.1109/ICDE65706.2026.00159	[ "Qian Xu", "Feng Zhang", "Shijie Gao", "Kun Chen", "Jianhua Wang", "Zheng Chen", "Xiaoyong Du" ]	Over the past decade, artificial intelligence (AI) has made remarkable strides, driven by researchers, engineers, and vendors who have relentlessly developed high-performance libraries across heterogeneous hardware and software. Recently, researchers in the database (DB) community have begun to harness this progress by...	#	ICDE2026
A Set-Theoretic Approach to Detecting Logic Bugs in DBMS Inner Join Optimizations	https://doi.org/10.1109/ICDE65706.2026.00224	[ "Ce Lyu", "Changzheng Wei", "Yanhao Wang", "Jie Liang", "Li Lin", "Hanghang Wu", "Minghao Zhao", "Ying Yan", "Aoying Zhou" ]	The query optimizer is a fundamental component of database management systems that determines the most efficient execution strategy for a given query by evaluating alternative query plans. Among its tasks, join optimization plays a central role, as the order of joins in multi-table queries can significantly affect exec...	#	ICDE2026
Community-Level Personalized Recommendation by Exploiting Evolving User-Item Micro-Clusters	https://doi.org/10.1109/ICDE65706.2026.00095	[ "Xinyu Liu", "Jinxia Guo", "Qirui Hao", "Zhongjing Yu", "Qinli Yang", "Junming Shao" ]	To achieve precise personalized recommendations, it is crucial to model user preference and item popularity simultaneously to capture their evolving characteristics. However, existing techniques often treat the evolution of user preference or item popularity with the same fixed decay rate, failing to capture the indivi...	#	ICDE2026
ARCADE: A Real-Time Data System for Hybrid and Continuous Query Processing Across Diverse Data Modalities	https://doi.org/10.1109/ICDE65706.2026.00255	[ "Jingyi Yang", "Songsong Mo", "Jiachen Shi", "Zihao Yu", "Kunhao Shi", "Xuchen Ding", "Gao Cong" ]	The explosive growth of multimodal data-spanning text, spatial, vector, and relational modalities, coupled with the need for real-time semantic search and retrieval over these data-has outpaced the capabilities of existing multimodal and real-time database systems, which either lack efficient ingestion and continuous q...	#	ICDE2026
Compressing High-Frequency Time Series Through Multiple Models and Stealing From Residuals	https://doi.org/10.1109/ICDE65706.2026.00025	[ "Abduvoris Abduvakhobov", "Søren Kejser Jensen", "Christian Thomsen", "Torben Bach Pedersen" ]	Wind turbines are equipped with high-quality sensors that generate vast volumes of high-frequency time series. The time series are ingested on the edge and transferred to the cloud for later analytics. This process is complicated by challenges like low network bandwidth and high cloud storage costs. ModelarDB was propo...	#	ICDE2026
DistVec: Efficient Distributed Machine Learning in Parallel Database Systems	https://doi.org/10.1109/ICDE65706.2026.00169	[ "Xinyi Zhang", "Liangzu Liu", "Xupeng Miao", "Yinjun Wu", "Zhen Chen", "Wei Lu", "Xiaoyong Du", "Bin Cui" ]	Embedding vectors are widely used in various database-related domains. However, efficiently training largescale embeddings directly on DB-resident data remains a challenge, despite the ongoing efforts on supporting machine learning algorithms in database management systems, known as in-DBMS ML. Although current UDAF-ba...	#	ICDE2026
Effective Dataset Distillation for Spatio-Temporal Forecasting with BI-Dimensional Compression	https://doi.org/10.1109/ICDE65706.2026.00131	[ "Taehyung Kwon", "Yeonje Choi", "Yeongho Kim", "Kijung Shin" ]	Spatio-temporal time series are widely used in realworld applications, including traffic prediction and weather forecasting. They are sequences of observations over extensive periods and multiple locations, naturally represented as multidimensional data. Forecasting is a central task in spatio-temporal analysis, and nu...	#	ICDE2026
FaScalSQL: A Fast and Scalable GPU-Accelerated SQL Query Engine for Out-of-Memory Tables	https://doi.org/10.1109/ICDE65706.2026.00009	[ "Chaemin Lim", "Suhyun Lee", "Jinwoo Choi", "Kwanghyun Park", "Jinho Lee", "Joonsung Kim", "Youngsok Kim" ]	Graphics Processing Units (GPUs) are promising for analytical SQL query processing, but their limited memory capacity hinders processing large input tables exceeding the GPU memory. The existing engines either 1) statically split input columns into chunks and iteratively perform host-to-GPU transfer and relational oper...	#	ICDE2026
GeminiSketch: An Accurate and Efficient Sketch for Summarizing Temporal Graph Streams with Rolling-Out Elimination	https://doi.org/10.1109/ICDE65706.2026.00010	[ "Xuyang Jing", "Chenhao Zhang", "Zheng Yan", "Qingze Jiang", "Witold Pedrycz", "Mingjun Wang", "Cong Wang" ]	A temporal graph stream represents a graph stream with dynamic behaviors, where the edges connecting vertices change over time. It can model a wide range of network behaviors, e.g., describing changes of subscribers in a social network, monitoring call duration within a mobile network. Analyzing the temporal graph stre...	#	ICDE2026
Fast Discovery of Functional Dependencies via Bayesian Network Learning	https://doi.org/10.1109/ICDE65706.2026.00011	[ "Siyi Yang", "Shenglin Chen", "Xi Wang", "Yuhua Tang", "Ruochun Jin" ]	Functional dependencies (FDs) are fundamental to data quality and query optimization. However, discovering highconfidence FDs from large-scale, noisy real-life datasets remains challenging, especially for those with low-support which can be early pruned. In view of this challenge, we propose BSFD, a scalable and parall...	#	ICDE2026
Approximate Butterfly Counting in Sublinear Time	https://doi.org/10.1109/ICDE65706.2026.00012	[ "Chi Luo", "Jiaxin Song", "Yuhao Zhang", "Kai Wang", "Zhixing He", "Kuan Yang" ]	Bipartite graphs serve as a natural model for representing relationships between two different types of entities. When analyzing bipartite graphs, butterfly counting is a fundamental research problem that aims to count the number of butterflies (i.e., 2×2 bicliques) in a given bipartite graph. While this problem has be...	#	ICDE2026
Exqutor: Extended Query Optimizer for Vector-Augmented Analytical Queries	https://doi.org/10.1109/ICDE65706.2026.00013	[ "Hyunjoon Kim", "Chaerim Lim", "Hyeonjun An", "Rathijit Sen", "Kwanghyun Park" ]	Vector similarity search is becoming increasingly important for data science pipelines, particularly in RetrievalAugmented Generation (RAG), where it enhances large language model inference by enabling efficient retrieval of relevant external knowledge. As RAG expands with table-augmented generation to incorporate stru...	#	ICDE2026
RoarChain: A Robust Sharding Blockchain System for Enterprise Consortium	https://doi.org/10.1109/ICDE65706.2026.00014	[ "Yuan Sui", "Xiaochun Yang", "Bin Wang", "Yujie Zhang", "Lina Wang" ]	Enterprise consortium blockchains are increasingly adopted in domains such as supply chains and finance, where secure, high-throughput data storage and verifiable, highly available query services are essential. While existing solutions like ScorpioBase leverage off-chain databases and fine-grained signatures to improve...	#	ICDE2026
Towards the Distributed Large-Scale $k$-NN Graph Construction by Graph Merge	https://doi.org/10.1109/ICDE65706.2026.00015	[ "Cheng Zhang", "Wan-Lei Zhao", "Shihai Xiao", "Jiajie Yao", "Xuecang Zhang" ]	In order to support the real-time interaction with LLMs and the instant search or the instant recommendation on social media, it becomes an imminent problem to build a $k$-NN graph or an indexing graph for the massive number of vectorized multimedia data. In such scenarios, the scale of the data or the scale of the gra...	#	ICDE2026
CSD-CoKV: Host-CSD Collaborative Offloading for High-Performance LSM-Tree Based KV Stores	https://doi.org/10.1109/ICDE65706.2026.00016	[ "Zhining Cao", "Kai Zhang", "Jinrun Yang", "Hui Li", "Nan Su", "Qian Wei", "Shikun Ma", "Zehao Chen", "Junbo Yin", "Haijun Zhang", "Zhaoyan Shen" ]	LSM-tree-based key-value stores are widely used due to their write efficiency and scalability. However, their background compaction process requires substantial data movement between the host and storage devices, resulting in inefficient resource usage, frequent write stalls, and degraded overall throughput. Existing o...	#	ICDE2026
Conflict Resolution for Improving ML Accuracy	https://doi.org/10.1109/ICDE65706.2026.00018	[ "Wenfei Fan", "Xiaoyu Han", "Hufsa Khan", "Weilong Ren", "Yaoshu Wang", "Min Xie", "Zihuan Xu" ]	This paper investigates how to make practical use of conflict resolution (CR) to enhance the accuracy of ML classifiers $\mathcal{M}$ on relational data. We show that applying CR to influential attributes and/or tuples can substantially improve the performance of downstream model $\mathcal{M}$. Based on this, we formul...	#	ICDE2026
MVGPT: Generative Materialized View Forecasting	https://doi.org/10.1109/ICDE65706.2026.00019	[ "Yue Han", "Guoliang Li", "Wenchun Xu", "Xianglei Ran", "Zeya Gong", "Wei Guo", "Guang Qiu", "Bo Zheng" ]	Existing materialized view (MV) selection methods rely on historical queries to select MVs. However, queries are dynamically and continually changing, and it is ineffective to generate MVs based only on historical queries. To address this limitation, we propose a novel MV forecasting framework, MVGPT, which utilizes la...	#	ICDE2026
Accurate Table Question Answering with Accessible LLMs	https://doi.org/10.1109/ICDE65706.2026.00020	[ "Yangfan Jiang", "Fei Wei", "Ergute Bao", "Yaliang Li", "Bolin Ding", "Yin Yang", "Xiaokui Xiao" ]	Given a table T in a database and a question Q in natural language, the table question answering (TQA) task aims to return an accurate answer to Q based on the content of T. Recent state-of-the-art solutions leverage large language models (LLMs) to obtain high-quality answers. However, most rely on proprietary, large-s...	#	ICDE2026
Autohformer: Efficient Hierarchical Autoregressive Transformer for Time Series Prediction	https://doi.org/10.1109/ICDE65706.2026.00021	[ "Qianru Zhang", "Honggang Wen", "Ming Li", "Dong Huang", "Siu-Ming Yiu", "Christian S. Jensen", "Pietro Liò" ]	Time series forecasting requires architectures that simultaneously achieve three competing objectives: (1) strict temporal causality for reliable predictions, (2) subquadratic complexity for practical scalability, and (3) multiscale pattern recognition for accurate long-horizon forecasting. We introduce AutoHFormer, a ...	https://github.com/CoderPowerBeyond/AutoHFormer	ICDE2026
CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness	https://doi.org/10.1109/ICDE65706.2026.00022	[ "Ying Zheng", "Yangfan Jiang", "Kian-Lee Tan" ]	Causal fairness in databases is crucial to preventing biased and inaccurate outcomes in downstream tasks. While most prior work assumes a known causal model, recent efforts relax this assumption by enforcing additional constraints. However, these approaches often fail to capture broader attribute relationships that are...	#	ICDE2026
Evolving Sketch: Time-Decaying Frequency Estimation for Evolving Streams	https://doi.org/10.1109/ICDE65706.2026.00023	[ "Ge Gao", "Yang Du", "He Huang", "Yu-E Sun", "Jianzhi Tang" ]	Frequency estimation approximates element occurrences using limited memory and is fundamental in data stream processing. Traditional probabilistic sketches provide spaceefficient solutions but treat all occurrences equally regardless of timing, causing suboptimal performance when recent observations matter more than hi...	#	ICDE2026
Contextual Pattern Mining and Counting	https://doi.org/10.1109/ICDE65706.2026.00024	[ "Ling Li", "Daniel Gibney", "Sharma V. Thankachan", "Solon P. Pissis", "Grigorios Loukides" ]	Given a string $P$ of length $m$, a longer string $T$ of length $n>m$, and two integers $l\geq 0$ and $r\geq 0$, the context of $P$ in $T$ is the set of all string pairs $(L,R)$, with $\|L\|=l$ and $\|R\|=r$, such that the string $LPR$ occurs in $T$. We introduce two problems related to the notion of context: (1) the Conte...	#	ICDE2026
A Unified Framework for Compressed and Encrypted Text Direct Processing	https://doi.org/10.1109/ICDE65706.2026.00026	[ "Yani Liu", "Feng Zhang", "Yu Zhang", "Siqi Ma", "Elisa Bertino", "Xiaoyong Du" ]	The rapid growth of textual data calls for systems that can efficiently manage large-scale text, while the need to safeguard text privacy has become increasingly urgent. Homomorphic encryption enables computation directly on encrypted data but incurs significant ciphertext expansion and high storage and computation cos...	#	ICDE2026
Spatiotemporal Sketch Disaggregation: Streaming Analytics with Heterogeneous Resources	https://doi.org/10.1109/ICDE65706.2026.00027	[ "Jonatan Langlet", "Peiqing Chen", "Michael Mitzenmacher", "Zaoxing Liu", "Ran Ben Basat", "Gianni Antichi" ]	Streaming analytics are essential in a large range of applications, including databases, networking, and machine learning. To optimize performance, practitioners are increasingly offloading such analytics to network nodes such as switches. However, resources such as fast SRAM memory available at switches are limited, n...	#	ICDE2026
L4g: Two-Hop Label Management for Group Steiner Tree Search on Graphs	https://doi.org/10.1109/ICDE65706.2026.00028	[ "Xiaoyao Feng", "Yahui Sun", "Zhuoran Wang", "Junlin Li", "Sijia Luo", "Rong-Hua Li" ]	Finding group Steiner trees (GSTs) is widely utilized for keyword search in relational databases. Current methods often build GSTs by querying and merging shortest paths. Some recent work explores the possibility of employing shortest path indexes, i.e., 2-hop labels, to speed up GST search, but fails to achieve a cons...	#	ICDE2026
Revisiting Locally Differentially Private Protocols: Towards Better Trade-Offs in Privacy, Utility, and Attack Resistance	https://doi.org/10.1109/ICDE65706.2026.00029	[ "Héber Hwang Arcolezi", "Sébastien Gambs" ]	Local Differential Privacy (LDP) offers strong privacy protection, especially in settings in which the server collecting the data is untrusted. However, designing LDP mechanisms that achieve an optimal trade-off between privacy, utility and robustness to adversarial inference and integrity attacks remains challenging. ...	#	ICDE2026
Micro: a Lightweight Middleware for Optimizing Cross-Store Cross-Model Graph-Relation Joins	https://doi.org/10.1109/ICDE65706.2026.00030	[ "Xiuwen Zheng", "Arun Kumar", "Amarnath Gupta" ]	Modern data applications increasingly involve heterogeneous data managed in different models and stored across disparate database engines, often deployed as separate installs. Limited research has addressed cross-model query processing in federated environments. This paper takes a step toward bridging this gap by: (1) ...	#	ICDE2026
Switch$\Delta$: Asynchronous Metadata Updating for Distributed Storage with in-Network Data Visibility	https://doi.org/10.1109/ICDE65706.2026.00031	[ "Junru Li", "Qing Wang", "Zhe Yang", "Shuo Liu", "Jiwu Shu", "Youyou Lu" ]	Distributed storage systems typically maintain strong consistency between data nodes and metadata nodes by adopting ordered writes: 1) first installing data; 2) then updating metadata to make data visible. We propose Switch $\Delta$ to accelerate ordered writes by moving metadata updates out of the critical path. It bu...	#	ICDE2026
DIndex: an Efficient on-Disk Learned Index for Memory-Constrained Environments	https://doi.org/10.1109/ICDE65706.2026.00032	[ "Jiahuan Shen", "Chuzhe Tang", "Haoning Lan", "Ren Ren", "Zhaoguo Wang" ]	B+trees, the de facto standard for on-disk database indexing, exhibit significant performance degradation in memoryconstrained environments due to frequent disk I/O that accesses out-of-cache index nodes during tree traversal. The recent proposal of in-memory learned indexes promises substantial reductions in index foo...	#	ICDE2026
Federated Retrieval Over Embedding-Heterogeneous Vector Databases	https://doi.org/10.1109/ICDE65706.2026.00033	[ "Yuxiang Wang", "Yongxin Tong", "Zimu Zhou", "Ziyuan He", "Ruixi Hu", "Ke Xu" ]	Vector databases are increasingly used to manage unstructured data by mapping them into high-dimensional embeddings and enabling efficient similarity retrieval. Many realworld applications, such as legal document retrieval and medical question answering, require embedding-based retrieval in federated environments where...	#	ICDE2026
LogDelta: Differential Encoding for Log Data	https://doi.org/10.1109/ICDE65706.2026.00034	[ "Songze Li", "Shaoxu Song", "Zhitao Shen" ]	System logs are critical for understanding the performance of various software systems. Compression is essential to efficient storage or transmission of system log data. Generalpurpose compressors like LZMA treat logs as binary data, ignoring their structure, and thus fail to achieve the best compression. The semi-stru...	#	ICDE2026
Secure Query Processing with Linear Online Cost	https://doi.org/10.1109/ICDE65706.2026.00035	[ "Qiyao Luo", "Yilei Wang", "Wei Dong", "Ke Yi" ]	Query processing under the secure multi-party computation (MPC) model has received increasing attention in recent years. However, all existing MPC query processing algorithms incur a cost of $\Omega(n \log n)$, due to the use of secure sorting. While secure sorting is believed to be inevitable, we observe that it can b...	#	ICDE2026
VisPoison: An Effective Backdoor Attack Framework for Tabular Data Visualization Models	https://doi.org/10.1109/ICDE65706.2026.00036	[ "Shuaimin Li", "Chen Jason Zhang", "Xuanang Chen", "Anni Peng", "Zhuoyue Wan", "Yuanfeng Song", "Shiwen Ni", "Min Yang", "Fei Hao", "Raymond Chi-Wing Wong" ]	Text-to-visualization (text-to-vis) models for tabular data have become essential tools in the era of big data, enabling users to generate visualizations and make data-driven decisions through natural language queries (NLQs). Despite their growing adoption, the security vulnerabilities of these models remain largely un...	#	ICDE2026
PRO-HNSW: Proactive Repair and Optimization for High-Performance Dynamic HNSW Indexes	https://doi.org/10.1109/ICDE65706.2026.00037	[ "Huijun Jin", "Jieun Lee", "Shengmin Piao", "Sangmin Seo", "Sanghyun Park" ]	Graph-based Approximate Nearest Neighbor Search (ANNS), particularly using Hierarchical Navigable Small World (HNSW) graphs, offers state-of-the-art query performance for large-scale, high-dimensional data. However, the efficiency and accuracy of HNSW indexes degrade seriously under dynamic conditions involving frequen...	#	ICDE2026
Promoting Fairness in Information Access Within Social Networks	https://doi.org/10.1109/ICDE65706.2026.00038	[ "Changan Liu", "Xiaotian Zhou", "Ahad N. Zehmakan", "Zhongzhi Zhang" ]	The advent of online social networks has facilitated fast and wide spread of information. However, some users, especially members of minority groups, may be less likely to receive information spreading on the network, due to their disadvantaged network position. We study the optimization problem of adding new connectio...	#	ICDE2026
Keyword-Aware Skyline Community Search on Semantics and Structure	https://doi.org/10.1109/ICDE65706.2026.00039	[ "Chuanhou Sun", "Yuhai Zhao", "Ling Li", "Yuan Li" ]	Community search (CS) on attributed graphs has been widely studied, catering to various applications such as friend recommendation. Recent works have focused on keywordaware community search with query keywords $Q$, aiming to return the closely connected communities relating to $\boldsymbol{Q}$. To achieve the best rec...	#	ICDE2026
$\mathrm{B}^{S}$-Tree: A Gapped Data-Parallel B-Tree	https://doi.org/10.1109/ICDE65706.2026.00040	[ "Dimitrios Tsitsigkos", "Achilleas Michalopoulos", "Nikos Mamoulis", "Manolis Terrovitis" ]	We propose $\mathbf{B}^{S}$-tree, an in-memory implementation of the $\mathbf{B}^{+}$-tree that adopts the structure of the disk-based index (i.e., a balanced, multiway tree), setting the node size to a memory block that can be processed fast and in parallel using SIMD instructions. A novel feature of the $\mathbf{B}^{...	#	ICDE2026
Zero-Knowledge Verifiable Graph Query Evaluation via Expansion-Centric Operator Decomposition	https://doi.org/10.1109/ICDE65706.2026.00041	[ "Hao Wu", "Changzheng Wei", "Yanhao Wang", "Li Lin", "Yilong Leng", "Shiyu He", "Minghao Zhao", "Hanghang Wu", "Ying Yan", "Aoying Zhou" ]	This paper investigates the feasibility of achieving zero-knowledge verifiability for graph databases, which enables data owners to cryptographically prove the correctness of query execution without disclosing the underlying graph data. Although similar capabilities for the verification of SQL query execution in relati...	#	ICDE2026
cuFHEDB: GPU-Accelerated Fully Homomorphic Encryption Database	https://doi.org/10.1109/ICDE65706.2026.00042	[ "Shijie Gao", "Feng Zhang", "Qian Xu", "Yang Li", "XueFeng Liu", "Chao Jiang", "Limin Xiao", "Siqi Ma", "Elisa Bertino", "Xiaoyong Du" ]	As data privacy becomes increasingly critical, fully homomorphic encryption (FHE) emerges as a promising solution for securely outsourcing database queries to the cloud without exposing plaintext information. However, FHE-based databases suffer from significant computational latency, obstructing efficient SQL query exe...	https://github.com/SekaiGao/cuFHEDB	ICDE2026
Contemp: Instance Caching Based on Container Temperature in Serverless Environment	https://doi.org/10.1109/ICDE65706.2026.00043	[ "Pengwei Wang", "Nuo Chen", "Haoquan Qi", "Yichen Zhong", "Shun Song" ]	In serverless computing, cloud providers dynamically manage the underlying resource allocation, allowing developers to concentrate on business logic development. Although containers ensure runtime consistency, creation and destruction of instances significantly degrade performance by increasing cold start latency. A wi...	#	ICDE2026
TopFGL: A Topology-Aware and Distributionagnostic Federated Learning Framework Tackling Topological Heterogeneity on Graph Data	https://doi.org/10.1109/ICDE65706.2026.00044	[ "Junyang Wang", "Lan Zhang", "Yihang Cheng", "Mu Yuan", "Tian Wang", "Zhihui Fu", "Jun Wang" ]	While the modern internet generates graph data at an unprecedented scale, stringent privacy regulations like GDPR have fragmented it into silos, creating an urgent need for distributed learning paradigms. Federated Graph Learning (FGL) meets this demand, enabling collaborative training across graph silos. A core challe...	#	ICDE2026
OsmT: Bridging Openstreetmap Queries and Natural Language With Open-Source Tag-Aware Language Models	https://doi.org/10.1109/ICDE65706.2026.00045	[ "Zhuoyue Wan", "Wentao Hu", "Chen Jason Zhang", "Yuanfeng Song", "Shuaimin Li", "Ruiqiang Xiao", "Xiao-Yong Wei", "Raymond Chi-Wing Wong" ]	Bridging natural language and structured query languages is a long-standing challenge in the database community. While recent advances in language models have shown promise in this direction, existing solutions often rely on large-scale closed-source models that suffer from high inference costs, limited transparency, a...	#	ICDE2026
Knapsack Optimization-Based Schema Linking for LLM-Based Text-to-SQL Generation	https://doi.org/10.1109/ICDE65706.2026.00046	[ "Zheng Yuan", "Hao Chen", "Zijin Hong", "Qinggang Zhang", "Feiran Huang", "Qing Li", "Xiao Huang" ]	Generating SQLs from user queries is a longstanding challenge, where the accuracy of initial schema linking significantly impacts subsequent SQL generation performance. However, current schema linking models still struggle with missing relevant schema elements or an excess of redundant ones. A crucial reason for this i...	https://github.com/DEEP-PolyU/KaSLA	ICDE2026
FLASH Viterbi: Fast and Adaptive Viterbi Decoding for Modern Data Systems	https://doi.org/10.1109/ICDE65706.2026.00047	[ "Ziheng Deng", "Xue Liu", "Jiantong Jiang", "Yankai Li", "Qingxu Deng", "Xiaochun Yang" ]	The Viterbi algorithm is a key operator for structured sequence inference in modern data systems, with applications in trajectory analysis, online recommendation, and speech recognition. As these workloads increasingly migrate to resource-constrained edge platforms, standard Viterbi decoding remains memory-intensive an...	https://github.com/Dzh-16/FLASH-Viterbi	ICDE2026
Sorting Compressed Time Series	https://doi.org/10.1109/ICDE65706.2026.00048	[ "Zhiheng Liu", "Xingyu Liu", "Shaoxu Song", "Jianmin Wang" ]	Compression is commonly used to reduce storage costs in large-scale time series databases. While time series data should be ordered by timestamps, they often arrive out of order due to network delay and thus need to be sorted. However, most existing compression schemes do not support direct swap operations on compresse...	#	ICDE2026
Reverse K Nearest Neighbor Query in Large Road Networks: a Tree Decomposition Based Approach	https://doi.org/10.1109/ICDE65706.2026.00049	[ "Dian Ouyang", "Boyu Zhang", "Jianye Yang", "Shiyu Yang", "Chonghua Wang", "Xuemin Lin" ]	Reverse k-nearest neighbor (R $k$ NN) query in road networks is an important and fundamental problem. Given a facility query vertex $q$, an $\mathrm{R} k \text{NN}$ query asks for finding all user vertices such that each of them regards $q$ as one of the $k$ nearest neighbors $(k \text{NN})$. Although $\mathbf{R} k \ma...	#	ICDE2026
Benchmarking RL-Enhanced Spatial Indices Against Traditional, Advanced, and Learned Counterparts	https://doi.org/10.1109/ICDE65706.2026.00050	[ "Guanli Liu", "Renata Borovica-Gajic", "Hai Lan", "Zhifeng Bao" ]	Reinforcement learning has recently been used to enhance index structures, giving rise to reinforcement learning-enhanced spatial indices (RLESIs) that aim to improve query efficiency during index construction. However, their practical benefits remain unclear due to the lack of unified implementations and comprehensive...	#	ICDE2026
ProGQL: A Provenance Graph Query System for Cyber Attack Investigation	https://doi.org/10.1109/ICDE65706.2026.00051	[ "Fei Shao", "Jia Zou", "Zhichao Cao", "Xusheng Xiao" ]	Provenance analysis (PA) has recently emerged as an important solution for cyber attack investigation. PA leverages system monitoring to monitor system activities as a series of system audit events and organizes these events as a provenance graph to show the dependencies among system activities, which can reveal steps ...	#	ICDE2026
Efficient Hypergraph Pattern Matching via Match-and-Filter and Intersection Constraint	https://doi.org/10.1109/ICDE65706.2026.00052	[ "Siwoo Song", "Wonseok Shin", "Kunsoo Park", "Giuseppe F. Italiano", "Zhengyi Yang", "Wenjie Zhang" ]	A hypergraph is a generalization of a graph, in which a hyperedge can connect multiple vertices, modeling complex relationships involving multiple vertices simultaneously. Hypergraph pattern matching, which is to find all isomorphic embeddings of a query hypergraph in a data hypergraph, is one of the fundamental proble...	#	ICDE2026
Trading Vector Data in Vector Databases	https://doi.org/10.1109/ICDE65706.2026.00053	[ "Jin Cheng", "Xiangxiang Dai", "Ningning Ding", "John C. S. Lui", "Jianwei Huang" ]	Vector data trading is essential for cross-domain learning with vector databases, yet it remains largely unexplored. We study this problem under online learning, where sellers face uncertain retrieval costs and buyers provide stochastic feedback to posted prices. Three main challenges arise: heterogeneous and partial f...	#	ICDE2026
Updatable Balanced Index for Fast on-Device Search with Auto-Selection Model	https://doi.org/10.1109/ICDE65706.2026.00054	[ "Yushuai Ji", "Sheng Wang", "Zhiyu Chen", "Yuan Sun", "Zhiyong Peng" ]	Diverse types of edge data, such as 2D geo-locations and 3D point clouds, are collected by sensors like lidar and GPS receivers on edge devices. On-device searches, such as $k$-nearest neighbor $(k \text{NN})$ search and radius search, are commonly used to enable fast analytics and learning technologies, such as kmeans...	#	ICDE2026
Banknote-Chain: Achieving User-Incentivized Parallelism in Blockchain via a Banknote-Inspired Transaction Model	https://doi.org/10.1109/ICDE65706.2026.00055	[ "Zhiyu Ma", "Xiaofeng Li", "He Zhao", "Tong Zhou", "Nianzu Sheng", "Haotian Cheng" ]	Scalability remains a fundamental bottleneck in blockchain, hindering its widespread adoption in highthroughput and large-scale applications. Existing research usually attempts to enhance performance through various on-chain algorithms. However, these methods can introduce significant computing overhead for analysis an...	#	ICDE2026
Efficient Zero-Shot and Label-free Log Anomaly Detection for Resource-Constrained Systems	https://doi.org/10.1109/ICDE65706.2026.00056	[ "Zuohan Wu", "Jiachuan Wang", "Libin Zheng", "Yongqi Zhang", "Shuangyin Li", "Lei Chen" ]	Logs, generated from modern computational systems such as cloud servers or DBMS, are the primary indicator of system states and thus have drawn significant attention from researchers. One of its key tasks is log anomaly detection, aiming to discover anomalous signals that can subsequently imply errors in systems. Conve...	#	ICDE2026
Energy-Efficient Autonomous Driving With Adaptive Perception and Robust Decision	https://doi.org/10.1109/ICDE65706.2026.00057	[ "Yuyang Xia", "Zibo Liang", "Liwei Deng", "Yan Zhao", "Han Su", "Kai Zheng" ]	Autonomous driving is an emerging technology that is expected to bring significant social, economic, and environmental benefits. However, these benefits come with rising energy consumption by computation engines, limiting the driving range of vehicles, especially electric ones. Perception computing is typically the mos...	#	ICDE2026
Mitigating Dual Load Imbalance via Dynamic Cooperative Scheduling in Distributed Key-Value Stores	https://doi.org/10.1109/ICDE65706.2026.00058	[ "Jiakun Zhang", "Patrick P. C. Lee", "Wenzhe Zhu", "Yongkun Li", "Shuyi Zhang", "Yinlong Xu" ]	Distributed key-value (KV) stores are essential components of modern computing infrastructure, enabling efficient storage and management of large-scale datasets. Existing distributed KV stores often shard data by key ranges into multiple regions and distribute the regions across multiple nodes. However, such range-base...	#	ICDE2026
MOCHI: Motif-Based Community Search Over Large Heterogeneous Information Networks	https://doi.org/10.1109/ICDE65706.2026.00059	[ "Yuhan Zhou", "Qing Liu", "Xin Huang", "Jianliang Xu", "Yunjun Gao" ]	In this paper, we investigate the problem of motif-based community search over heterogeneous information networks (MOCHI). We introduce a novel motif density modularity (MDM) to measure the motif cohesiveness of communities. Based on MDM, we define the MOCHI problem as follows: given a heterogeneous information network...	#	ICDE2026
Reconfiguring Scalable Hashing with Persistent CPU Caches	https://doi.org/10.1109/ICDE65706.2026.00060	[ "Zhenyu Yu", "Bolong Zheng", "Ling Xu", "Qianlu Wu", "Qiang Chen", "Ziyang Yue" ]	As an essential functionality in main memory system, the extendible hash index exhibits both low latency and instant recovery with the persistent memory (PM). The recently released eADR feature of PM further provides an opportunity to enhance write performance of extendible hash index. Compared to the previous generati...	#	ICDE2026
TemplateQO: Template-Aware and Scalable Query Optimization with Data-Efficient Learning	https://doi.org/10.1109/ICDE65706.2026.00061	[ "Pengfei Zheng", "Guoneng Li", "Ling Xu", "Rong Zhu", "Yan Li", "Bolong Zheng" ]	Learning-based query optimizers have demonstrated strong performance across various scenarios. However, most of these approaches rely heavily on estimated cardinalities, and inaccuracies in these estimates may significantly degrade their effectiveness in certain cases. Moreover, in our experiments we observe as the tra...	#	ICDE2026
Query-Driven Data Exploration with Heterogeneous Treatment Effects	https://doi.org/10.1109/ICDE65706.2026.00062	[ "Antonis Mandamadiotis", "Sihem Amer-Yahia", "Georgia Koutrika" ]	Understanding how changes in actions or policies impact different population segments (users, items, etc.) is central to data-driven decision-making, but it is time-consuming and labor-intensive. We introduce a novel framework that combines user-defined search areas with causal inference to automatically identify respo...	#	ICDE2026
SOLAR: Scalable Distributed Spatial Joins Through Learning-Based Optimization	https://doi.org/10.1109/ICDE65706.2026.00063	[ "Yongyi Liu", "Ahmed Abdelmaguid", "Ahmed R. Mahmood", "Amr Magdy", "Minyao Zhu" ]	The proliferation of location-based services has led to massive spatial data generation. Spatial join is a crucial database operation that identifies pairs of objects from two spatial datasets based on spatial relationships. Due to the intensive computational demands, spatial joins are often executed in a distributed m...	#	ICDE2026
Interpreting Graph Inference with Skyline Explanations	https://doi.org/10.1109/ICDE65706.2026.00064	[ "Dazhuo Qiu", "Haolai Che", "Arijit Khan", "Yinghui Wu" ]	Inference queries have been routinely issued to graph machine learning models such as graph neural networks (GNNs) for various network analytical tasks. Nevertheless, GNN outputs are often hard to interpret comprehensively. Existing methods typically conform to individual pre-defined explainability measures (such as fi...	#	ICDE2026
Chase Anonymisation: Privacy-Preserving Knowledge Graphs with Logical Reasoning	https://doi.org/10.1109/ICDE65706.2026.00065	[ "Luigi Bellomarini", "Costanza Catalano", "Andrea Coletta", "Michela Iezzi", "Pierangela Samarati" ]	We propose a novel framework to enable Knowledge Graphs (KGs) sharing while ensuring that information that should remain private is not directly released nor indirectly exposed via derived knowledge, maintaining at the same time the embedded knowledge of the KGs to support business downstream tasks. Our approach produc...	#	ICDE2026
SSC-Join: An Efficient Syntactic-Semantic Collaboration Based Set Semantic Similarity Join Algorithm	https://doi.org/10.1109/ICDE65706.2026.00066	[ "Lianyin Jia", "Chengchen Zeng", "Mengjuan Li", "Suprio Ray", "Yinong Chen", "Jiaman Ding", "Xiuxing Li" ]	Existing semantic similarity join algorithms assume that all elements in the sets are semantic elements, overlooking the significant impact of syntactic elements. Processing semantic elements requires executing the Hungarian algorithm, leading to high processing costs. To address this challenge, we first introduce sign...	#	ICDE2026
Deferred Flushing for Out-of-Order Arrivals in Apache IoTDB	https://doi.org/10.1109/ICDE65706.2026.00067	[ "Xiaojian Zhang", "Zhiheng Liu", "Shaoxu Song", "Xiangdong Huang", "Chen Wang", "Jianmin Wang" ]	Delays are inevitably associated with network transmission, leading to out-of-order time series arrivals. To store the data in time order, time series databases (TSDBs) choose to merge them via compaction in an LSM-tree. It incurs huge write amplification cost. We notice that the out-of-order arrivals are often delayed...	#	ICDE2026
Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution	https://doi.org/10.1109/ICDE65706.2026.00068	[ "Kaiqi Wu", "Weiyang Kong", "Sen Zhang", "Zitong Chen", "Yubao Liu" ]	Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To model the complex spatial-temporal dependencies in traffic data, Spatial-Temporal Graph Convolutional Networks (STGCNs) have been widely employed, achieving advanced performance. How...	https://github.com/wkq-wukaiqi/RAGC	ICDE2026
SaSPartitioner: A Self-Adaptive Streaming Partitioner Using Deep Reinforcement Learning	https://doi.org/10.1109/ICDE65706.2026.00069	[ "Shenghao Gong", "Liu Liu", "Ziquan Fang", "Yunjun Gao", "Yaofeng Tu" ]	Stream processing has been widely adopted in online services, such as e-commerce platforms and real-time query systems, due to its ability to leverage distributed parallel computing for low-latency, large-scale data processing. However, data skew, which results in imbalanced load distribution across computational nodes...	#	ICDE2026
AdaFedRec: Adaptive Heterogeneous Federated Recommender Systems Across Multi-Device Users	https://doi.org/10.1109/ICDE65706.2026.00070	[ "Zhenkai Li", "Ming Hu", "Chentao Jia", "Yining Sun", "Zhufeng Lu", "Mingyang Yu", "Yanxin Yang", "Xiaofei Xie", "Mingsong Chen" ]	Although Federated Learning (FL), as a distributed machine learning paradigm, is promising for privacy-preserving model training in recommender systems, it suffers from low training performance due to heterogeneous hardware resources across user devices, especially among users with multiple devices. Specifically, i) th...	https://github.com/Iridescentttttt/AdaFedRec	ICDE2026
MatKV: Trading Compute for Flash Storage in LLM Inference	https://doi.org/10.1109/ICDE65706.2026.00071	[ "Kunwoo Shin", "Jay H. Park", "Moonwook Oh", "Yohan Jo", "Jaeyoung Do", "Sang-Won Lee" ]	We observe two major trends in LLM-based generative AI: (1) inference is becoming the dominant factor in terms of cost and power consumption, surpassing training, and (2) retrieval augmented generation (RAG) is becoming prevalent. When processing long inputs in RAG, the prefill phase of computing the key-value vectors ...	https://github.com/kunwooshin/MatKV	ICDE2026
LUCID: An Updatable and Concurrent Learned Index for Larger-Than-Memory Data Management	https://doi.org/10.1109/ICDE65706.2026.00072	[ "Chaohong Ma", "Xiaohui Yu", "Yifan Li", "Aishan Maoliniyazi", "Xiaofeng Meng" ]	Learned indexes have shown great potential for improving data storage and access performance, but their adoption in real-world systems is limited when data exceed memory capacity. In-memory approaches become impractical at scale, while fully on-disk techniques often fail to meet the performance demands of diverse workl...	#	ICDE2026
CoLSE: A Lightweight and Robust Hybrid Learned Model for Single-Table Cardinality Estimation Using Joint CDF	https://doi.org/10.1109/ICDE65706.2026.00073	[ "Lankadinee Rathuwadu", "Guanli Liu", "Christopher Leckie", "Renata Borovica-Gajic" ]	Cardinality estimation (CE), the task of predicting the result size of queries is a critical component of query optimization. Accurate estimates are essential for generating efficient query execution plans. Recently, machine learning techniques have been applied to CE, broadly categorized into query-driven and data-dri...	#	ICDE2026
An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data	https://doi.org/10.1109/ICDE65706.2026.00074	[ "Buang Zhang", "Tung Kieu", "Xiangfei Qiu", "Chenjuan Guo", "Jilin Hu", "Aoying Zhou", "Christian S. Jensen", "Bin Yang" ]	Time series anomaly detection is important in modern large-scale systems and is applied in a variety of domains to analyze and monitor the operation of diverse systems. Unsupervised approaches have received widespread interest, as they do not require anomaly labels during training, thus avoiding potentially high costs ...	#	ICDE2026
Grace: Alleviating Reconstruction Cost in Dynamic Graph Processing Systems	https://doi.org/10.1109/ICDE65706.2026.00075	[ "Hongru Gao", "Shuhao Zhang", "Xiaofei Liao", "Hai Jin" ]	Efficient dynamic graph processing is critical for real-time applications. Recent systems utilize hybrid layouts combining Packed Memory Array (PMA) and Compressed Sparse Row (CSR) structures to balance updating and computing efficiency. However, these systems face key challenges, including costly global copying and tr...	#	ICDE2026
High-Fidelity Task Assignment in Spatial Crowdsourcing via Implicit Human Feedback	https://doi.org/10.1109/ICDE65706.2026.00076	[ "Qingshun Wu", "Yafei Li", "Lei Gao", "Guanglei Zhu", "Lei Chen", "Mingliang Xu" ]	Dynamic task assignment that allocates spatial tasks to mobile workers based on time windows has emerged as a key research problem in spatial crowdsourcing (SC), where the major challenge lies in deciding the optimal window size. Recent studies use reinforcement learning models (RLMs) to adaptively partition task strea...	#	ICDE2026
LAMP: A Dual-Mode Framework for Database Workload Memory Prediction	https://doi.org/10.1109/ICDE65706.2026.00077	[ "Guoze Xue", "Lu Chen", "Ziquan Fang", "Yushuai Li", "Tianyi Li", "Torben Bach Pedersen" ]	Precise prediction of working memory consumption for query workloads is crucial for preventing out-of-memory errors and optimizing resource utilization in modern database systems. While existing approaches focus on performance prediction for individual queries, they fail to capture the complex memory dynamics arising f...	#	ICDE2026
Efficient Model-Agnostic Continual Learning for Next POI Recommendation	https://doi.org/10.1109/ICDE65706.2026.00078	[ "Chenhao Wang", "Shanshan Feng", "Lisi Chen", "Fan Li", "Shuo Shang" ]	Next point-of-interest (POI) recommendation improves personalized location-based services by predicting users' next destinations based on their historical check-ins. However, most existing methods rely on static datasets and fixed models, limiting their ability to adapt to changes in user behavior over time. To address...	#	ICDE2026
GeoLayer: Towards Low-Latency and Cost-Efficient Geo-Distributed Graph Stores with Layered Graph	https://doi.org/10.1109/ICDE65706.2026.00079	[ "Feng Yao", "Xiaokang Yang", "Shufeng Gong", "Song Yu", "Yanfeng Zhang", "Ge Yu" ]	The inherent connectivity and dependency of graphstructured data, combined with its unique topology-driven access patterns, pose fundamental challenges to conventional data replication and request routing strategies in geo-distributed cloud storage systems. In this paper, we propose GeoLayer, a geodistributed graph sto...	#	ICDE2026
Robust Index Benefit Estimation via Hierarchical and Two-Dimensional Feature Representation	https://doi.org/10.1109/ICDE65706.2026.00080	[ "Tao Li", "Feng Liang", "Jinqi Quan", "Zihang Yang", "Teng Wang", "Runhuai Huang", "Xiping Hu", "Meng Li", "Haipeng Dai" ]	In recent years, machine learning-based index advisors have gained success as they can estimate the benefit of a given index without actually evaluating it via what-if optimizers. However, existing methods often fail to capture indexrelevant features adequately, leading to limited accuracy and poor adaptability to chan...	https://github.com/quanjnq/Eddie	ICDE2026
MTC: Scalable Transaction Commit for Multi-Primary Cloud Databases	https://doi.org/10.1109/ICDE65706.2026.00081	[ "Kecheng Luo", "Xiaoxian Wei", "Wenxin Liu", "Peng Cai", "Aoying Zhou", "Hui Li", "Le Cai" ]	While compute-storage disaggregation provides elasticity to cloud databases, the prevalent single-primary model restricts write scalability and fault tolerance. Maintaining data consistency becomes a key challenge when multiple primaries handle concurrent writes, especially with hot data cached locally. This paper pres...	#	ICDE2026
EC-RAG: Towards Efficient Edge-Cloud Retrieval-Augmented Generation Systems	https://doi.org/10.1109/ICDE65706.2026.00082	[ "Liang Wang", "Kai Wang", "Ranjun Jia", "Kai Lu", "Jiguang Wan", "Hao Huo", "Yulong Zhai", "Zhiyuan Liang", "Di Wang" ]	Retrieval-augmented generation (RAG) grounds the desired responses of large language models (LLMs) by connecting to external knowledge databases. However, deploying full-scale LLMs on resource-constrained edge servers is impractical. Instead, small language models (SLMs) enable efficient deployment at the edge, but the...	#	ICDE2026
TabLoft: Tabular Data Generation Based on LLM with Ordered Features	https://doi.org/10.1109/ICDE65706.2026.00083	[ "Luyu Chen", "Changhao Wu", "Jingyi Li", "Sen Liu", "Guangnan Ye", "Hongfeng Chai" ]	Tabular data is a fundamental format for storage and processing in databases. However, it often suffers from challenges such as limited sample size and privacy concerns in specific tasks. Tabular data generation offers a promising solution, and methods based on large language models (LLMs) have demonstrated strong perf...	#	ICDE2026
CYANSQL: Unlock the Power of NL2SQL Via Clustering-Based Test-Time Scaling	https://doi.org/10.1109/ICDE65706.2026.00084	[ "Haoyu Qin", "Tonghui Ren", "Zhenying He", "X. Sean Wang", "Jiashu Xing", "Yanghuan Ye", "Shifei Huang", "Jinbao Li" ]	Large language models (LLMs) are playing an increasingly important role in the Natural Language to SQL (NL2SQL) task. Although LLMs exhibit strong inherent reasoning abilities, they often fail to generate correct SQL because they lack knowledge of the target logical operator composition. Few-shot learning is a commonly...	https://github.com/zyddqhy/CYANSQL	ICDE2026
Effective Fairest Community Search Over Heterogeneous Information Networks	https://doi.org/10.1109/ICDE65706.2026.00085	[ "Taige Zhao", "Jianxin Li", "Man Li", "Wei Luo", "Jingxian Cheng", "Yuan Miao", "Hua Wang" ]	Community search over heterogeneous information networks has been applied to wide domains, such as activity organization and team formation. Existing studies focus on identifying groups of members that meet the minimum engagement requirements. But in reality, given a group, its members may exhibit large gaps in their e...	#	ICDE2026
Iit-Tree: an Efficient Index to Support Interval-Based Query on Large Temporal Graphs	https://doi.org/10.1109/ICDE65706.2026.00086	[ "Faming Li", "Shengli Qiu", "Xiaochun Yang", "Bin Wang", "Hengzhao Ma" ]	Graph is a powerful model to represent many-tomany relationships between entities and is widely used in mining social networks, managing communication networks, etc. The networks are usually not static and change over time. One of these types of networks is always represented by temporal graph, whose edges or vertices ...	#	ICDE2026
PORCA: Root Cause Analysis with Partially Observed Data	https://doi.org/10.1109/ICDE65706.2026.00087	[ "Chang Gong", "Di Yao", "Jin Wang", "Wenbin Li", "Lanting Fang", "Yongtao Xie", "Kaiyu Feng", "Peng Han", "Jingping Bi" ]	Root Cause Analysis (RCA), aiming at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from collected time-series databases, has been widely used in many application domains. However, previous studies implicitly assume a full observation of the system and neglect the ef...	#	ICDE2026
Efficient and Scalable Search for Statistics	https://doi.org/10.1109/ICDE65706.2026.00088	[ "Antoine Gauquier", "Simon Ebel", "Helena Galhardas", "Théo Galizzi", "Ioana Manolescu", "Aurélien Peden", "Pierre Senellart" ]	Informed public debate needs high-quality data. In this context, high-quality statistical data sources are a valuable category of reference information based on which a claim can be checked. To facilitate the work of journalists or other factcheckers, users' questions about a specific claim should be automatically answ...	#	ICDE2026
Reconstructing TensorLog for Scalable End-to-End Rule Learning	https://doi.org/10.1109/ICDE65706.2026.00089	[ "Kunxun Qi", "Jianfeng Du", "Hai Wan", "Wei Wang" ]	Logical rules play a crucial role in knowledge graph (KG) reasoning. They underpin various database applications and serve as pivotal components for enhancing large language models (LLMs) with KGs. In recent years, end-to-end rule learning has emerged as a promising paradigm to learn logical rules. The key insight of e...	#	ICDE2026
HL-Index: Fast Reachability Query in Hypergraphs	https://doi.org/10.1109/ICDE65706.2026.00090	[ "Peiting Xie", "Xiangjun Zai", "Yanping Wu", "Xiaoyang Wang", "Wenjie Zhang", "Lu Qin" ]	Reachability in hypergraphs is essential for modeling complex groupwise interactions in real-world applications such as co-authorship, social network, and biological analysis, where relationships go beyond pairwise interactions. In this paper, we introduce the notion of $\boldsymbol{s}$-reachability, where two vertices...	#	ICDE2026
Astraea: Efficient Pipelined Micro-Batch Stream Processing with Non-Hash Differentiated Partitioning	https://doi.org/10.1109/ICDE65706.2026.00091	[ "Sijie Wu", "Hanhua Chen", "Hai Jin", "Haoran Cai" ]	Modern micro-batch stream processing systems have emerged to meet the requirement of real-time stream processing with extreme throughput. They leverage two-stage pipeline parallelism which overlaps stream buffering and data processing to speed up the system, while relying on a functional parallel computation framework ...	#	ICDE2026
Trajectory-User Linking via Heterogeneous Preference Graph and Dual-Encoder Mutual Distillation	https://doi.org/10.1109/ICDE65706.2026.00092	[ "Zeming Tian", "Zixin Qin", "Huaijie Zhu", "Ningning Cui", "Wei Liu", "Jianxing Yu", "Jian Yin" ]	Trajectory User Linking (TUL) is a critical task in spatio-temporal behavior analysis, which focuses on reidentifying users from anonymous mobility traces. While prior approaches have made progress by modeling the sequential patterns and behavioral dynamics of trajectories, they often neglect the heterogeneous semantic...	https://github.com/Ledingburger/HPG-DEMD	ICDE2026
PC-PS: A Multi-Dimensional Point-Cloud Data Publish/Subscribe System	https://doi.org/10.1109/ICDE65706.2026.00093	[ "Yuanchi Fan", "Lisi Chen", "Shuo Shang", "Christian S. Jensen" ]	With continued advances in LiDAR technologies, massive volumes of point-cloud data are being collected for use in an expanding range of applications. Point-cloud data include geographic coordinates along with additional attributes such as intensity and timestamp, enabling fine-grained modeling of urban and natural envi...	https://github.com/fanyuanchi/PointCloud.git	ICDE2026
TransLGX: A Self-Contained Model to Predict the Entire Lifecycle and Complete State of Logistics Package Trajectories	https://doi.org/10.1109/ICDE65706.2026.00094	[ "Yichen Song", "Jianfeng Zhou", "Jian-Ya Ding", "Renhao Cao" ]	This paper presents a novel logistics package trajectory prediction approach. This approach breaks away from the traditional Markov assumption for the first time by capturing the dynamic changes of the logistics network from previous trajectory events and covers the entire lifecycle and complete state of logistics pack...	https://github.com/Scholar-Song/TransLGX/blob/main/	ICDE2026
SHMemora: Protective Key-Value Store on Distributed Shared Memory	https://doi.org/10.1109/ICDE65706.2026.00096	[ "Jiajun Luo", "Siyu Lin", "Yunpeng Xu", "Shengwei Liu", "Jin Xia", "Dong Liu", "Zheng Liu", "Huanchen Zhang", "Teng Ma", "Shuwen Deng" ]	Modern in-memory key-value stores (IMKVS) are essential for data-intensive applications but increasingly limited by memory capacity. Traditional scale-out over TCP/IP or RDMA incurs high overhead from network latency and data movement. Emerging Compute Express Link (CXL) enables nearlocal-latency shared memory across h...	#	ICDE2026

End of preview. Expand in Data Studio

PaperVault Dataset · 论文元数据库

🔎 项目简介 · Overview

PaperVault 是一份持续自动更新的统一论文元数据库，覆盖自然语言处理、计算机视觉、机器学习、数据挖掘、数据库、语音、系统、网络、安全、理论计算机科学、人机交互、计算机图形学与多媒体等方向的顶级会议与期刊。PaperVault is a continuously-updated, unified metadata database of papers from top-tier conferences and journals across NLP, Computer Vision, Machine Learning, Data Mining, Databases, Speech, Systems, Networking, Security, Theory, HCI, Graphics, and Multimedia.

🌐 源仓库 / Source: github.com/youngfish42/PaperVault — Web UI、REST API、采集流水线、Issues / PRs 全部在那里 · Web UI, REST API, crawling pipelines and issues/PRs all live there.

🌐 在线搜索 / Live search: papervault.top — 直接使用 Web 检索界面，无需下载数据 · Use the web search UI directly without downloading the dataset.

🆕 最近更新 · Recent Update

📅 最近更新 · Last updated: 2026-09-01 (Asia/Shanghai)
📊 数据库规模 · Database size: 650,459 篇论文 / 120 个刊物系列 / 553,153 篇含摘要 / 43,026 篇含开源代码（650,459 papers / 120 venue series / 553,153 with abstract / 43,026 with code）

📈 数据看板 · Statistics at a Glance

下列 4 张统计图与 cache.jsonl.gz 同源同步，反映本数据集的最新状态。The four charts below are generated from the same cache.jsonl.gz and always reflect the latest state of this dataset.

Statistics Overview

Papers by Research Field

Annual Paper Collection Trend

Publication Series Word Cloud

📦 数据集内容 · What's in this dataset

路径 Path	子集 Subset	格式 Format	说明 Description
`cache/cache.jsonl.gz`	`papers`（默认 / default）	gzip-compressed JSON Lines (UTF-8)	每行一篇论文 · One paper per line; one JSON object per line
`cache/abstract_backfill_progress.jsonl.gz`	`abstract_backfill_progress`	gzip-compressed JSON Lines (UTF-8)	摘要回填流水线的进度/断点记录，不是论文元数据；仅供工作流恢复使用 · Append-only progress log of the abstract-backfill pipeline (not paper records); used by the workflow to resume between runs

Hugging Face 会自动为 cache.jsonl.gz 生成 Parquet 视图，也可直接用 datasets.load_dataset(...) 读取，无需手动解压。Hugging Face also exposes an auto-generated Parquet view, so datasets.load_dataset(...) works out of the box.

💡 Dataset Viewer 与 datasets.load_dataset("youngfish42/PaperVault") 默认展示/加载的都是 papers 子集（即 cache/cache.jsonl.gz）。如需查看回填进度，请在 Viewer 顶部下拉框切换到 abstract_backfill_progress，或调用 load_dataset("youngfish42/PaperVault", name="abstract_backfill_progress")。The Dataset Viewer and datasets.load_dataset("youngfish42/PaperVault") both default to the papers subset (cache/cache.jsonl.gz). To inspect backfill progress, switch the Viewer's subset dropdown to abstract_backfill_progress or call load_dataset("youngfish42/PaperVault", name="abstract_backfill_progress").

📐 字段 Schema

Field 字段	Type 类型	Notes 说明
`paper_name`	string	论文标题（已归一化）· Normalised paper title
`paper_authors`	list[string]	作者列表，按原始顺序 · Author names in order
`paper_url`	string	论文在原始平台的链接（PDF 或落地页）· Canonical URL on the venue's site (PDF or landing page)
`paper_abstract`	string	摘要；未回填时为空字符串 · Abstract; may be empty when not yet backfilled
`paper_code`	string	从摘要中抽取出的 GitHub 仓库 URL；`"#"` 是「未发现代码链接」的占位符 · GitHub repository URL extracted from the abstract; `"#"` is the sentinel for "no code link discovered"
`conf`	string	会议+年份标识，如 `ACL2024`、`NIPS2023`、`CVPR2025`；去掉末尾四位数字即可得到会议系列。注意 NeurIPS Proceedings 沿用历史命名 `NIPS{year}`。Venue + year identifier (e.g. `ACL2024`, `NIPS2023`, `CVPR2025`). Strip the trailing 4-digit year to recover the venue series. Note that NeurIPS Proceedings entries use the historical name `NIPS{year}`.

缺失字段请按空字符串处理。Treat missing fields as empty strings.

⬇️ 获取方式 · How to download

下面三种方式任选其一即可，无需克隆 GitHub 仓库。Pick any one of the three options below — no GitHub clone is required.

方式 A · Option A — `huggingface_hub`（推荐 / recommended）

from huggingface_hub import hf_hub_download
import gzip, json

path = hf_hub_download(
    repo_id="youngfish42/PaperVault",
    filename="cache/cache.jsonl.gz",
    repo_type="dataset",
)

with gzip.open(path, "rt", encoding="utf-8") as f:
    for line in f:
        record = json.loads(line)
        # 在这里处理一条记录 · do something with the record

方式 B · Option B — `datasets`

from datasets import load_dataset

ds = load_dataset("youngfish42/PaperVault")
print(ds[next(iter(ds))][0])

数据集只有一个默认 split（非 ML 训练集），不要传 split="train"。Single default split — do not pass split="train".

方式 C · Option C — `huggingface-cli` / 直接 HTTPS · Plain HTTPS

huggingface-cli download youngfish42/PaperVault \
    cache/cache.jsonl.gz --repo-type dataset --local-dir ./data

💡 文件压缩后约 120 MB（会随数据持续增长），解压后是 GB 级 JSONL 流，请按行流式读取，不要整体载入内存。The file is ~120 MB compressed (and growing) and decompresses to a multi-GB JSONL stream. Stream it line-by-line rather than loading the whole thing into memory.

🔁 更新节奏 · Update cadence

数据集由三个 GitHub Actions 工作流负责重建并推送到本 Hub 仓库 / The dataset is rebuilt and pushed to this Hub repo by three GitHub Actions workflows：

工作流 Workflow	触发节奏 Schedule	推送的内容 What it pushes
`collect_papers`	每月 15 号 16:00 UTC + 手动触发 · 15th of every month at 16:00 UTC + `workflow_dispatch`	增量抓取新发现的会议/年份组合 · Incremental crawl of newly-discovered conference/year combinations
`backfill_abstracts`	每月 1 号 00:00 UTC + 手动触发 · 1st of every month at 00:00 UTC + `workflow_dispatch`	为已有论文回填 `paper_abstract` · Adds `paper_abstract` for papers that were collected without one
`update_readme`	仅手动触发 (`workflow_dispatch`) · Manual only (`workflow_dispatch`)	默认仅刷新 README 与统计；当输入参数 `mode=force` 时执行全量重建 · Refreshes the README and statistics by default; performs a full rebuild only when invoked with `mode=force`

每次推送都使用 Hugging Face 的 parent_commit 乐观锁机制，避免并发覆盖。Each push uses Hugging Face's parent_commit optimistic-lock mechanism to avoid silently overwriting concurrent updates.

🌐 线上服务 · Live Service

无需下载数据集即可直接体验 Web 检索： No need to download the dataset — try the web search directly:

👉 papervault.top

🔗 关联仓库 · Related repository

如果你需要完整的搜索 Web UI（智能搜索 + Web of Science 风格的高级查询 DSL）、REST API（/api/v1/*）、抓取 / 合并 / 摘要回填流水线源码、收录会议范围、统计仪表盘、项目截图或贡献指南，请前往 GitHub 项目仓库。If you are looking for the full search Web UI (smart search + Web-of-Science-style advanced query DSL), the REST API (/api/v1/*), the crawling / merging / abstract-backfill pipelines source code, conference coverage, statistics dashboards, screenshots or contribution guidelines, please visit the GitHub repository.

👉 github.com/youngfish42/PaperVault

📜 许可证 · License

代码以 GPL-3.0 发布；每条论文记录的著作权仍属于原作者 / 出版方，本数据集仅重新分发公开可获取的元数据与链接。Code is released under GPL-3.0; individual paper records remain the IP of their authors/publishers — this dataset only redistributes publicly available bibliographic metadata and links.