SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Dian, Peng, Baolin, Tian, Ye, Song, Linfeng, Mi, Haitao, Yu, Dong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
by: Tian, Ye, et al.
Published: (2024)
by: Tian, Ye, et al.
Published: (2024)
Entropy Guided Extrapolative Decoding to Improve Factuality in Large Language Models
by: Das, Souvik, et al.
Published: (2024)
by: Das, Souvik, et al.
Published: (2024)
Fine-Grained Self-Endorsement Improves Factuality and Reasoning
by: Wang, Ante, et al.
Published: (2024)
by: Wang, Ante, et al.
Published: (2024)
Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning
by: Wang, Xiyao, et al.
Published: (2024)
by: Wang, Xiyao, et al.
Published: (2024)
Self-Consistency Boosts Calibration for Math Reasoning
by: Wang, Ante, et al.
Published: (2024)
by: Wang, Ante, et al.
Published: (2024)
Collaborative decoding of critical tokens for boosting factuality of large language models
by: Jin, Lifeng, et al.
Published: (2024)
by: Jin, Lifeng, et al.
Published: (2024)
LiteSearch: Efficacious Tree Search for LLM
by: Wang, Ante, et al.
Published: (2024)
by: Wang, Ante, et al.
Published: (2024)
Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
by: Zhang, Yuheng, et al.
Published: (2024)
by: Zhang, Yuheng, et al.
Published: (2024)
Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration Pitfalls
by: Wang, Ante, et al.
Published: (2025)
by: Wang, Ante, et al.
Published: (2025)
Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation
by: Zhang, Xiaoying, et al.
Published: (2024)
by: Zhang, Xiaoying, et al.
Published: (2024)
Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values
by: Yu, Dian, et al.
Published: (2025)
by: Yu, Dian, et al.
Published: (2025)
Conceptual and Unbiased Reasoning in Language Models
by: Zhou, Ben, et al.
Published: (2024)
by: Zhou, Ben, et al.
Published: (2024)
Teaching LLMs to Refine with Tools
by: Yu, Dian, et al.
Published: (2024)
by: Yu, Dian, et al.
Published: (2024)
DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
by: He, Zhiwei, et al.
Published: (2025)
by: He, Zhiwei, et al.
Published: (2025)
Teaching Language Models to Self-Improve through Interactive Demonstrations
by: Yu, Xiao, et al.
Published: (2023)
by: Yu, Xiao, et al.
Published: (2023)
Self-Tuning: Instructing LLMs to Effectively Acquire New Knowledge through Self-Teaching
by: Zhang, Xiaoying, et al.
Published: (2024)
by: Zhang, Xiaoying, et al.
Published: (2024)
Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
by: Zhang, Yuheng, et al.
Published: (2025)
by: Zhang, Yuheng, et al.
Published: (2025)
Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation
by: Zhou, Yujun, et al.
Published: (2025)
by: Zhou, Yujun, et al.
Published: (2025)
Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains
by: Su, Yi, et al.
Published: (2025)
by: Su, Yi, et al.
Published: (2025)
CLUE: Non-parametric Verification from Experience via Hidden-State Clustering
by: Liang, Zhenwen, et al.
Published: (2025)
by: Liang, Zhenwen, et al.
Published: (2025)
Evaluating Intermediate Reasoning of Code-Assisted Large Language Models for Mathematics
by: Al-Khalili, Zena, et al.
Published: (2025)
by: Al-Khalili, Zena, et al.
Published: (2025)
CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
by: Dai, Runpeng, et al.
Published: (2025)
by: Dai, Runpeng, et al.
Published: (2025)
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
by: Zhang, Zhihan, et al.
Published: (2024)
by: Zhang, Zhihan, et al.
Published: (2024)
Inconsistent dialogue responses and how to recover from them
by: Zhang, Mian, et al.
Published: (2024)
by: Zhang, Mian, et al.
Published: (2024)
DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search
by: Yue, Murong, et al.
Published: (2024)
by: Yue, Murong, et al.
Published: (2024)
Dual-Uncertainty Guided Policy Learning for Multimodal Reasoning
by: Liu, Rui, et al.
Published: (2025)
by: Liu, Rui, et al.
Published: (2025)
A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
by: Li, Xiangci, et al.
Published: (2024)
by: Li, Xiangci, et al.
Published: (2024)
Dancing with Critiques: Enhancing LLM Reasoning with Stepwise Natural Language Self-Critique
by: Li, Yansi, et al.
Published: (2025)
by: Li, Yansi, et al.
Published: (2025)
A Survey on Large Language Models for Mathematical Reasoning
by: Wang, Peng-Yuan, et al.
Published: (2025)
by: Wang, Peng-Yuan, et al.
Published: (2025)
Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models
by: Li, Miaoran, et al.
Published: (2023)
by: Li, Miaoran, et al.
Published: (2023)
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
by: Chen, Jiaao, et al.
Published: (2023)
by: Chen, Jiaao, et al.
Published: (2023)
Scaling Synthetic Data Creation with 1,000,000,000 Personas
by: Ge, Tao, et al.
Published: (2024)
by: Ge, Tao, et al.
Published: (2024)
DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning
by: Zhang, Ziyin, et al.
Published: (2025)
by: Zhang, Ziyin, et al.
Published: (2025)
PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models
by: Yu, Ye, et al.
Published: (2025)
by: Yu, Ye, et al.
Published: (2025)
Save the Good Prefix: Precise Error Penalization via Process-Supervised RL to Enhance LLM Reasoning
by: Liu, Haolin, et al.
Published: (2026)
by: Liu, Haolin, et al.
Published: (2026)
WebEvolver: Enhancing Web Agent Self-Improvement with Coevolving World Model
by: Fang, Tianqing, et al.
Published: (2025)
by: Fang, Tianqing, et al.
Published: (2025)
DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains
by: Liang, Tian, et al.
Published: (2025)
by: Liang, Tian, et al.
Published: (2025)
ReliableMath: Benchmark of Reliable Mathematical Reasoning on Large Language Models
by: Xue, Boyang, et al.
Published: (2025)
by: Xue, Boyang, et al.
Published: (2025)
VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models
by: Zhang, Ce, et al.
Published: (2025)
by: Zhang, Ce, et al.
Published: (2025)
Large Language Models Can Self-Improve in Long-context Reasoning
by: Li, Siheng, et al.
Published: (2024)
by: Li, Siheng, et al.
Published: (2024)
Similar Items
-
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
by: Tian, Ye, et al.
Published: (2024) -
Entropy Guided Extrapolative Decoding to Improve Factuality in Large Language Models
by: Das, Souvik, et al.
Published: (2024) -
Fine-Grained Self-Endorsement Improves Factuality and Reasoning
by: Wang, Ante, et al.
Published: (2024) -
Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning
by: Wang, Xiyao, et al.
Published: (2024) -
Self-Consistency Boosts Calibration for Math Reasoning
by: Wang, Ante, et al.
Published: (2024)