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Collections including paper arxiv:2508.20755

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
Universal Deep Research: Bring Your Own Model and Strategy

Paper • 2509.00244 • Published Aug 29 • 13

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28 • 63
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28 • 15
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10 • 56

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11

Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 133
Magistral

Paper • 2506.10910 • Published Jun 12 • 65
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs

Paper • 2506.07240 • Published Jun 8 • 7
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation

Paper • 2506.09991 • Published Jun 11 • 55

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning

Paper • 2509.02479 • Published Sep 2 • 83
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28 • 15
THOR: Tool-Integrated Hierarchical Optimization via RL for Mathematical Reasoning

Paper • 2509.13761 • Published Sep 17 • 16

my paper collection

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning

Paper • 2508.15868 • Published Aug 21 • 3
Gated Delta Networks: Improving Mamba2 with Delta Rule

Paper • 2412.06464 • Published Dec 9, 2024 • 14

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models

Paper • 2508.10751 • Published Aug 14 • 28
Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 263
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 158

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 529 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
Universal Deep Research: Bring Your Own Model and Strategy

Paper • 2509.00244 • Published Aug 29 • 13

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning

Paper • 2509.02479 • Published Sep 2 • 83
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28 • 15
THOR: Tool-Integrated Hierarchical Optimization via RL for Mathematical Reasoning

Paper • 2509.13761 • Published Sep 17 • 16

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28 • 63
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28 • 15
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10 • 56

my paper collection

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11
CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning

Paper • 2508.15868 • Published Aug 21 • 3
Gated Delta Networks: Improving Mamba2 with Delta Rule

Paper • 2412.06464 • Published Dec 9, 2024 • 14

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28 • 11

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models

Paper • 2508.10751 • Published Aug 14 • 28
Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 263
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 158

Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 133
Magistral

Paper • 2506.10910 • Published Jun 12 • 65
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs

Paper • 2506.07240 • Published Jun 8 • 7
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation

Paper • 2506.09991 • Published Jun 11 • 55

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 529 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

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