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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 24
Collections
Discover the best community collections!
Collections including paper arxiv:2504.03553
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VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Paper • 2504.05118 • Published • 26 -
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models
Paper • 2504.04718 • Published • 41 -
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Paper • 2504.03561 • Published • 18 -
Concept Lancet: Image Editing with Compositional Representation Transplant
Paper • 2504.02828 • Published • 17
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R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Paper • 2503.10615 • Published • 17 -
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Paper • 2503.10630 • Published • 6 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 35 -
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL
Paper • 2503.07536 • Published • 89
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MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Paper • 2502.14499 • Published • 193 -
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
Paper • 2502.14739 • Published • 106 -
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?
Paper • 2502.14502 • Published • 91 -
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Paper • 2502.14282 • Published • 27
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End-to-End Goal-Driven Web Navigation
Paper • 1602.02261 • Published -
Learning Language Games through Interaction
Paper • 1606.02447 • Published -
Naturalizing a Programming Language via Interactive Learning
Paper • 1704.06956 • Published -
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Paper • 1802.08802 • Published • 1
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 63 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 121 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 114 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 139
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Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 83 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 57 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 24
-
End-to-End Goal-Driven Web Navigation
Paper • 1602.02261 • Published -
Learning Language Games through Interaction
Paper • 1606.02447 • Published -
Naturalizing a Programming Language via Interactive Learning
Paper • 1704.06956 • Published -
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Paper • 1802.08802 • Published • 1
-
VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Paper • 2504.05118 • Published • 26 -
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models
Paper • 2504.04718 • Published • 41 -
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Paper • 2504.03561 • Published • 18 -
Concept Lancet: Image Editing with Compositional Representation Transplant
Paper • 2504.02828 • Published • 17
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 63 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 121 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 114 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 139
-
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Paper • 2503.10615 • Published • 17 -
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Paper • 2503.10630 • Published • 6 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 35 -
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL
Paper • 2503.07536 • Published • 89
-
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 83 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 57 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
-
MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Paper • 2502.14499 • Published • 193 -
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
Paper • 2502.14739 • Published • 106 -
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?
Paper • 2502.14502 • Published • 91 -
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Paper • 2502.14282 • Published • 27