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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 496 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2509.23808
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BroRL: Scaling Reinforcement Learning via Broadened Exploration
Paper • 2510.01180 • Published • 18 -
MITS: Enhanced Tree Search Reasoning for LLMs via Pointwise Mutual Information
Paper • 2510.03632 • Published • 41 -
Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
Paper • 2509.25849 • Published • 47 -
Beyond the Exploration-Exploitation Trade-off: A Hidden State Approach for LLM Reasoning in RLVR
Paper • 2509.23808 • Published • 47
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Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 9 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46 -
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85
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Meta-Awareness Enhances Reasoning Models: Self-Alignment Reinforcement Learning
Paper • 2510.03259 • Published • 57 -
Hybrid Reinforcement: When Reward Is Sparse, It's Better to Be Dense
Paper • 2510.07242 • Published • 30 -
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Paper • 2510.08308 • Published • 24 -
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 75
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Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 70 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 22 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 496 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
-
Meta-Awareness Enhances Reasoning Models: Self-Alignment Reinforcement Learning
Paper • 2510.03259 • Published • 57 -
Hybrid Reinforcement: When Reward Is Sparse, It's Better to Be Dense
Paper • 2510.07242 • Published • 30 -
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Paper • 2510.08308 • Published • 24 -
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 75
-
BroRL: Scaling Reinforcement Learning via Broadened Exploration
Paper • 2510.01180 • Published • 18 -
MITS: Enhanced Tree Search Reasoning for LLMs via Pointwise Mutual Information
Paper • 2510.03632 • Published • 41 -
Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
Paper • 2509.25849 • Published • 47 -
Beyond the Exploration-Exploitation Trade-off: A Hidden State Approach for LLM Reasoning in RLVR
Paper • 2509.23808 • Published • 47
-
Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 70 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 22 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
-
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 9 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46 -
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85