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Collections including paper arxiv:2406.11896

Embodiment enables interaction of model with environment. Key is to anticipate what change could've come with its current action.

Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation

Paper • 2408.11812 • Published Aug 21, 2024 • 6
WebArena: A Realistic Web Environment for Building Autonomous Agents

Paper • 2307.13854 • Published Jul 25, 2023 • 25
Agent Workflow Memory

Paper • 2409.07429 • Published Sep 11, 2024 • 32
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale

Paper • 2409.08264 • Published Sep 12, 2024 • 48

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Paper • 2406.11896 • Published Jun 14, 2024 • 20

Foundation AI Papers (II)

Iterative Reasoning Preference Optimization

Paper • 2404.19733 • Published Apr 30, 2024 • 49
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30, 2024 • 81
ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12, 2024 • 70
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30, 2024 • 116

How Far Are We from Intelligent Visual Deductive Reasoning?

Paper • 2403.04732 • Published Mar 7, 2024 • 21
MoAI: Mixture of All Intelligence for Large Language and Vision Models

Paper • 2403.07508 • Published Mar 12, 2024 • 77
DragAnything: Motion Control for Anything using Entity Representation

Paper • 2403.07420 • Published Mar 12, 2024 • 14
Learning and Leveraging World Models in Visual Representation Learning

Paper • 2403.00504 • Published Mar 1, 2024 • 33

Reinforcement Learning (RL / RLHF)

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13, 2024 • 71
Understanding and Diagnosing Deep Reinforcement Learning

Paper • 2406.16979 • Published Jun 23, 2024 • 10
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4, 2024 • 62
Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning

Paper • 2407.00617 • Published Jun 30, 2024 • 7

a collection of algorithmic agents for user interfaces/interactions, program synthesis, and robotics

about 11 hours ago

End-to-End Goal-Driven Web Navigation

Paper • 1602.02261 • Published Feb 6, 2016
Learning Language Games through Interaction

Paper • 1606.02447 • Published Jun 8, 2016
Naturalizing a Programming Language via Interactive Learning

Paper • 1704.06956 • Published Apr 23, 2017
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Paper • 1802.08802 • Published Feb 24, 2018 • 1

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Paper • 2412.14161 • Published Dec 18, 2024 • 51
Training Software Engineering Agents and Verifiers with SWE-Gym

Paper • 2412.21139 • Published Dec 30, 2024 • 24
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis

Paper • 2412.19723 • Published Dec 27, 2024 • 87
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Paper • 2408.00764 • Published Aug 1, 2024 • 1

Embodiment enables interaction of model with environment. Key is to anticipate what change could've come with its current action.

Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation

Paper • 2408.11812 • Published Aug 21, 2024 • 6
WebArena: A Realistic Web Environment for Building Autonomous Agents

Paper • 2307.13854 • Published Jul 25, 2023 • 25
Agent Workflow Memory

Paper • 2409.07429 • Published Sep 11, 2024 • 32
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale

Paper • 2409.08264 • Published Sep 12, 2024 • 48

Reinforcement Learning (RL / RLHF)

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13, 2024 • 71
Understanding and Diagnosing Deep Reinforcement Learning

Paper • 2406.16979 • Published Jun 23, 2024 • 10
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4, 2024 • 62
Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning

Paper • 2407.00617 • Published Jun 30, 2024 • 7

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Paper • 2406.11896 • Published Jun 14, 2024 • 20

a collection of algorithmic agents for user interfaces/interactions, program synthesis, and robotics

about 11 hours ago

End-to-End Goal-Driven Web Navigation

Paper • 1602.02261 • Published Feb 6, 2016
Learning Language Games through Interaction

Paper • 1606.02447 • Published Jun 8, 2016
Naturalizing a Programming Language via Interactive Learning

Paper • 1704.06956 • Published Apr 23, 2017
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Paper • 1802.08802 • Published Feb 24, 2018 • 1

Foundation AI Papers (II)

Iterative Reasoning Preference Optimization

Paper • 2404.19733 • Published Apr 30, 2024 • 49
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30, 2024 • 81
ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12, 2024 • 70
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30, 2024 • 116

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Paper • 2412.14161 • Published Dec 18, 2024 • 51
Training Software Engineering Agents and Verifiers with SWE-Gym

Paper • 2412.21139 • Published Dec 30, 2024 • 24
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis

Paper • 2412.19723 • Published Dec 27, 2024 • 87
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Paper • 2408.00764 • Published Aug 1, 2024 • 1

How Far Are We from Intelligent Visual Deductive Reasoning?

Paper • 2403.04732 • Published Mar 7, 2024 • 21
MoAI: Mixture of All Intelligence for Large Language and Vision Models

Paper • 2403.07508 • Published Mar 12, 2024 • 77
DragAnything: Motion Control for Anything using Entity Representation

Paper • 2403.07420 • Published Mar 12, 2024 • 14
Learning and Leveraging World Models in Visual Representation Learning

Paper • 2403.00504 • Published Mar 1, 2024 • 33

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