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Hammer: Robust Function-Calling for On-Device Language Models via Function Masking
Paper • 2410.04587 • Published • 2 -
TaskCraft: Automated Generation of Agentic Tasks
Paper • 2506.10055 • Published • 32 -
Direct Multi-Turn Preference Optimization for Language Agents
Paper • 2406.14868 • Published -
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers
Paper • 2508.20453 • Published • 63
Collections
Discover the best community collections!
Collections including paper arxiv:2509.01055
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RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 123 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
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Let LLMs Break Free from Overthinking via Self-Braking Tuning
Paper • 2505.14604 • Published • 23 -
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios
Paper • 2505.16944 • Published • 8 -
Training Step-Level Reasoning Verifiers with Formal Verification Tools
Paper • 2505.15960 • Published • 7 -
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Paper • 2505.15134 • Published • 6
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Hammer: Robust Function-Calling for On-Device Language Models via Function Masking
Paper • 2410.04587 • Published • 2 -
TaskCraft: Automated Generation of Agentic Tasks
Paper • 2506.10055 • Published • 32 -
Direct Multi-Turn Preference Optimization for Language Agents
Paper • 2406.14868 • Published -
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers
Paper • 2508.20453 • Published • 63
-
Let LLMs Break Free from Overthinking via Self-Braking Tuning
Paper • 2505.14604 • Published • 23 -
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios
Paper • 2505.16944 • Published • 8 -
Training Step-Level Reasoning Verifiers with Formal Verification Tools
Paper • 2505.15960 • Published • 7 -
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Paper • 2505.15134 • Published • 6
-
RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 123 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25