:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lu, Sidi, Liang, Zhenwen, Ma, Dongyang, Wang, Yan, Mi, Haitao, Yu, Dong
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2602.05085
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Group Distributionally Robust Optimization-Driven Reinforcement Learning for LLM Reasoning
by: Panaganti, Kishan, et al.
Published: (2026)

Save the Good Prefix: Precise Error Penalization via Process-Supervised RL to Enhance LLM Reasoning
by: Liu, Haolin, et al.
Published: (2026)

CLUE: Non-parametric Verification from Experience via Hidden-State Clustering
by: Liang, Zhenwen, et al.
Published: (2025)

Guided Self-Evolving LLMs with Minimal Human Supervision
by: Yu, Wenhao, et al.
Published: (2025)

Verified Critical Step Optimization for LLM Agents
by: Li, Mukai, et al.
Published: (2026)

Free(): Learning to Forget in Malloc-Only Reasoning Models
by: Zheng, Yilun, et al.
Published: (2026)

EconProver: Towards More Economical Test-Time Scaling for Automated Theorem Proving
by: Li, Mukai, et al.
Published: (2025)

Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation
by: Zhou, Yujun, et al.
Published: (2025)

DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification
by: Liu, Rui, et al.
Published: (2026)

Recall with Reasoning: Chain-of-Thought Distillation for Mamba's Long-Context Memory and Extrapolation
by: Ma, Junyu, et al.
Published: (2025)

Stable and Efficient Single-Rollout RL for Multimodal Reasoning
by: Liu, Rui, et al.
Published: (2025)

The End of Manual Decoding: Towards Truly End-to-End Language Models
by: Wang, Zhichao, et al.
Published: (2025)

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
by: Dai, Runpeng, et al.
Published: (2025)

Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data
by: Liang, Zhenwen, et al.
Published: (2026)

HDFlow: Enhancing LLM Complex Problem-Solving with Hybrid Thinking and Dynamic Workflows
by: Yao, Wenlin, et al.
Published: (2024)

Dual-Uncertainty Guided Policy Learning for Multimodal Reasoning
by: Liu, Rui, et al.
Published: (2025)

DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning
by: Zhang, Ziyin, et al.
Published: (2025)

WebEvolver: Enhancing Web Agent Self-Improvement with Coevolving World Model
by: Fang, Tianqing, et al.
Published: (2025)

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
by: He, Zhiwei, et al.
Published: (2025)

Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
by: Liang, Zhenwen, et al.
Published: (2025)

Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
by: Zhang, Zhihan, et al.
Published: (2024)

SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models
by: Yu, Dian, et al.
Published: (2024)

Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training
by: Fang, Tianqing, et al.
Published: (2025)

Entropy Guided Extrapolative Decoding to Improve Factuality in Large Language Models
by: Das, Souvik, et al.
Published: (2024)

DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains
by: Liang, Tian, et al.
Published: (2025)

VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models
by: Zhang, Ce, et al.
Published: (2025)

Inconsistent dialogue responses and how to recover from them
by: Zhang, Mian, et al.
Published: (2024)

Scaling Synthetic Data Creation with 1,000,000,000 Personas
by: Ge, Tao, et al.
Published: (2024)

Using LLM to select the right SQL Query from candidates
by: Li, Zhenwen, et al.
Published: (2024)

Teaching LLMs to Refine with Tools
by: Yu, Dian, et al.
Published: (2024)

WebRollback: Enhancing Web Agents with Explicit Rollback Mechanisms
by: Zhang, Zhisong, et al.
Published: (2025)

Block-Attention for Efficient Prefilling
by: Ma, Dongyang, et al.
Published: (2024)

A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
by: Li, Xiangci, et al.
Published: (2024)

Collaborative decoding of critical tokens for boosting factuality of large language models
by: Jin, Lifeng, et al.
Published: (2024)

Don't Throw Away Your Pretrained Model
by: Feng, Shangbin, et al.
Published: (2025)

Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values
by: Yu, Dian, et al.
Published: (2025)

Towards Solving More Challenging IMO Problems via Decoupled Reasoning and Proving
by: Liang, Zhenwen, et al.
Published: (2025)

Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens
by: Ouyang, Xu, et al.
Published: (2024)

DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search
by: Yue, Murong, et al.
Published: (2024)

Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
by: Liu, Xiaoyuan, et al.
Published: (2025)