Cover Image

Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Zhihan, Ge, Tao, Liang, Zhenwen, Yu, Wenhao, Yu, Dian, Jia, Mengzhao, Yu, Dong, Jiang, Meng
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training
by: Jia, Mengzhao, et al.
Published: (2024)

Prioritizing the Best: Incentivizing Reliable Multimodal Reasoning by Rewarding Beyond Answer Correctness
by: Jia, Mengzhao, et al.
Published: (2026)

PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning
by: Zhang, Zhihan, et al.
Published: (2023)

Leopard: A Vision Language Model For Text-Rich Multi-Image Tasks
by: Jia, Mengzhao, et al.
Published: (2024)

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas
by: Wang, Xiaoyang, et al.
Published: (2025)

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

MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions
by: Liang, Zhenwen, et al.
Published: (2024)

MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems
by: Zhu, Zifeng, et al.
Published: (2024)

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

AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning
by: Jia, Mengzhao, et al.
Published: (2025)

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

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

Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples
by: Zeng, Qingkai, et al.
Published: (2024)

RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph
by: Ouyang, Siru, et al.
Published: (2024)

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

Conceptual and Unbiased Reasoning in Language Models
by: Zhou, Ben, et al.
Published: (2024)

Enhancing Mathematical Reasoning in LLMs by Stepwise Correction
by: Wu, Zhenyu, 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)

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

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

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

MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring
by: Yang, Tengchao, et al.
Published: (2025)

The Reasoning-Memorization Interplay in Language Models Is Mediated by a Single Direction
by: Hong, Yihuai, et al.
Published: (2025)

Forward-Backward Reasoning in Large Language Models for Mathematical Verification
by: Jiang, Weisen, et al.
Published: (2023)

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

Locas: Your Models are Principled Initializers of Locally-Supported Parametric Memories
by: Lu, Sidi, et al.
Published: (2026)

Self-Rewarding Vision-Language Model via Reasoning Decomposition
by: Li, Zongxia, et al.
Published: (2025)

Implicit Probabilistic Reasoning Does Not Reflect Explicit Answers in Large Language Models
by: Mondal, Manuel, et al.
Published: (2024)

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

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

Thinking Out of Order: When Output Order Stops Reflecting Reasoning Order in Diffusion Language Models
by: Yu, Longxuan, et al.
Published: (2026)

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

Revisiting Anthropomorphic Reflection Markers in Large Language Model Reasoning
by: Yu, Yahan, et al.
Published: (2026)

Cognitive Loop of Thought: Reversible Hierarchical Markov Chain for Efficient Mathematical Reasoning
by: Zhang, Jia-Chen, et al.
Published: (2026)

Efficient Mathematical Reasoning Models via Dynamic Pruning and Knowledge Distillation
by: Yu, Fengming, et al.
Published: (2025)

Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective
by: Yu, Yiyao, et al.
Published: (2025)

A Survey on Large Language Models for Mathematical Reasoning
by: Wang, Peng-Yuan, et al.
Published: (2025)

Prophet: Prompting Large Language Models with Complementary Answer Heuristics for Knowledge-based Visual Question Answering
by: Yu, Zhou, et al.
Published: (2023)

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

Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
by: Chen, Jiaao, et al.
Published: (2023)