Collections
Discover the best community collections!
Collections including paper arxiv:2504.21798
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One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 159 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 61
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TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks
Paper • 2412.14161 • Published • 52 -
Training Software Engineering Agents and Verifiers with SWE-Gym
Paper • 2412.21139 • Published • 24 -
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
Paper • 2412.19723 • Published • 88 -
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation
Paper • 2408.00764 • Published • 1
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I-Con: A Unifying Framework for Representation Learning
Paper • 2504.16929 • Published • 30 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 20 -
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
Paper • 2504.15785 • Published • 19 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 33
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CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
Paper • 2404.03543 • Published • 18 -
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Paper • 2406.11931 • Published • 66 -
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
Paper • 2407.18901 • Published • 35 -
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Paper • 2408.07060 • Published • 43
-
I-Con: A Unifying Framework for Representation Learning
Paper • 2504.16929 • Published • 30 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 20 -
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
Paper • 2504.15785 • Published • 19 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 33
-
One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 159 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 61
-
CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
Paper • 2404.03543 • Published • 18 -
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Paper • 2406.11931 • Published • 66 -
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
Paper • 2407.18901 • Published • 35 -
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Paper • 2408.07060 • Published • 43
-
TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks
Paper • 2412.14161 • Published • 52 -
Training Software Engineering Agents and Verifiers with SWE-Gym
Paper • 2412.21139 • Published • 24 -
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
Paper • 2412.19723 • Published • 88 -
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation
Paper • 2408.00764 • Published • 1