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Collections including paper arxiv:2505.17063

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10
Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models

Paper • 2505.17826 • Published May 23 • 9

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 299
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Paper • 2504.10479 • Published Apr 14 • 303
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models

Paper • 2503.24235 • Published Mar 31 • 54
Seedream 3.0 Technical Report

Paper • 2504.11346 • Published Apr 15 • 70

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Running on Zero

20

gryannote

🐰

20

Label speakers in audio recordings
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Paper • 2412.18319 • Published Dec 24, 2024 • 39
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs

Paper • 2501.06186 • Published Jan 10 • 65
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

Paper • 2505.07608 • Published May 12 • 82

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 262
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 133
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Paper • 2506.05176 • Published Jun 5 • 74
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 276

Distilling LLM Agent into Small Models with Retrieval and Code Tools

Paper • 2505.17612 • Published May 23 • 81
Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Paper • 2504.08837 • Published Apr 10 • 43
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model

Paper • 2504.10068 • Published Apr 14 • 30
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations

Paper • 2504.10481 • Published Apr 14 • 85

LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models

Paper • 2410.09732 • Published Oct 13, 2024 • 54
How to Synthesize Text Data without Model Collapse?

Paper • 2412.14689 • Published Dec 19, 2024 • 52
WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training

Paper • 2501.18511 • Published Jan 30 • 20
Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10

Reinforcement learning

Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning

Paper • 2407.20798 • Published Jul 30, 2024 • 24
Offline Reinforcement Learning for LLM Multi-Step Reasoning

Paper • 2412.16145 • Published Dec 20, 2024 • 38
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 103
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Paper • 2502.18449 • Published Feb 25 • 75

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 262
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 133
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Paper • 2506.05176 • Published Jun 5 • 74
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 276

Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10
Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models

Paper • 2505.17826 • Published May 23 • 9

Distilling LLM Agent into Small Models with Retrieval and Code Tools

Paper • 2505.17612 • Published May 23 • 81
Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 299
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Paper • 2504.10479 • Published Apr 14 • 303
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models

Paper • 2503.24235 • Published Mar 31 • 54
Seedream 3.0 Technical Report

Paper • 2504.11346 • Published Apr 15 • 70

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Paper • 2504.08837 • Published Apr 10 • 43
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model

Paper • 2504.10068 • Published Apr 14 • 30
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations

Paper • 2504.10481 • Published Apr 14 • 85

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models

Paper • 2410.09732 • Published Oct 13, 2024 • 54
How to Synthesize Text Data without Model Collapse?

Paper • 2412.14689 • Published Dec 19, 2024 • 52
WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training

Paper • 2501.18511 • Published Jan 30 • 20
Synthetic Data RL: Task Definition Is All You Need

Paper • 2505.17063 • Published May 18 • 10

Running on Zero

20

gryannote

🐰

20

Label speakers in audio recordings
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Paper • 2412.18319 • Published Dec 24, 2024 • 39
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs

Paper • 2501.06186 • Published Jan 10 • 65
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

Paper • 2505.07608 • Published May 12 • 82

Reinforcement learning

Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning

Paper • 2407.20798 • Published Jul 30, 2024 • 24
Offline Reinforcement Learning for LLM Multi-Step Reasoning

Paper • 2412.16145 • Published Dec 20, 2024 • 38
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 103
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Paper • 2502.18449 • Published Feb 25 • 75

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