Image de couverture de livre

Process In-Context Learning: Enhancing Mathematical Reasoning via Dynamic Demonstration Insertion

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Gao, Ang, Zhang, Changshuo, Zhang, Xiao, Li, Deyang, Zhao, Minjun, Liu, Fangchao, Zhang, Xinyu
Format:	Preprint
Publié:	2026
Sujets:	Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot
par: Cheng, Xiang, et autres
Publié: (2025)

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation
par: Zhang, Ziniu, et autres
Publié: (2025)

Understanding the Dynamics of Demonstration Conflict in In-Context Learning
par: Jiao, Difan, et autres
Publié: (2026)

ProcessBench: Identifying Process Errors in Mathematical Reasoning
par: Zheng, Chujie, et autres
Publié: (2024)

Enhancing In-Context Learning via Implicit Demonstration Augmentation
par: Zhou, Xiaoling, et autres
Publié: (2024)

Skill-Enhanced Reinforcement Learning Acceleration from Heterogeneous Demonstrations
par: Zhang, Hanping, et autres
Publié: (2024)

The Lessons of Developing Process Reward Models in Mathematical Reasoning
par: Zhang, Zhenru, et autres
Publié: (2025)

Escaping the Verifier: Learning to Reason via Demonstrations
par: Cai, Locke, et autres
Publié: (2025)

Learning to Select In-Context Demonstration Preferred by Large Language Model
par: Zhang, Zheng, et autres
Publié: (2025)

Efficient Mathematical Reasoning Models via Dynamic Pruning and Knowledge Distillation
par: Yu, Fengming, et autres
Publié: (2025)

CAMA: Enhancing Mathematical Reasoning in Large Language Models with Causal Knowledge
par: Zan, Lei, et autres
Publié: (2025)

Rethinking the Sampling Criteria in Reinforcement Learning for LLM Reasoning: A Competence-Difficulty Alignment Perspective
par: Kong, Deyang, et autres
Publié: (2025)

Variational Learning for Insertion-based Generation
par: Zhang, Yangtian, et autres
Publié: (2026)

Reasoning While Recommending: Entropy-Guided Latent Reasoning in Generative Re-ranking Models
par: Zhang, Changshuo
Publié: (2026)

How to Leverage Diverse Demonstrations in Offline Imitation Learning
par: Yue, Sheng, et autres
Publié: (2024)

Learning Quadruped Walking from Seconds of Demonstration
par: Zhang, Ruipeng, et autres
Publié: (2026)

Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning
par: Tan, Zelin, et autres
Publié: (2025)

More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
par: Zhang, Xiaoqing, et autres
Publié: (2025)

CORE: Concept-Oriented Reinforcement for Bridging the Definition-Application Gap in Mathematical Reasoning
par: Gao, Zijun, et autres
Publié: (2025)

DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs
par: Zhang, Yuanhe, et autres
Publié: (2025)

Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models
par: Chen, Changyu, et autres
Publié: (2024)

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification
par: Liu, Chengwu, et autres
Publié: (2025)

Integrating Attention-Enhanced LSTM and Particle Swarm Optimization for Dynamic Pricing and Replenishment Strategies in Fresh Food Supermarkets
par: Liu, Xianchen, et autres
Publié: (2025)

Unlocking Multimodal Mathematical Reasoning via Process Reward Model
par: Luo, Ruilin, et autres
Publié: (2025)

Bias-Restrained Prefix Representation Finetuning for Mathematical Reasoning
par: Liang, Sirui, et autres
Publié: (2025)

StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason
par: Zhang, Kaiyi, et autres
Publié: (2025)

FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models
par: Yu, Zhouliang, et autres
Publié: (2025)

Evaluating Long-Context Reasoning in LLM-Based WebAgents
par: Chung, Andy, et autres
Publié: (2025)

Agentic Proposing: Enhancing Large Language Model Reasoning via Compositional Skill Synthesis
par: Jiao, Zhengbo, et autres
Publié: (2026)

Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
par: Zhang, Jianqi, et autres
Publié: (2026)

Learn to Think: Bootstrapping LLM Reasoning Capability Through Graph Representation Learning
par: Gao, Hang, et autres
Publié: (2025)

Efficient On-Policy Reinforcement Learning via Exploration of Sparse Parameter Space
par: Zhang, Xinyu, et autres
Publié: (2025)

Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning
par: Yuan, Xinyu, et autres
Publié: (2026)

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning
par: Zheng, Congmin, et autres
Publié: (2025)

ADOPT: Adaptive Dependency-Guided Joint Prompt Optimization for Multi-Step LLM Pipelines
par: Zhao, Minjun, et autres
Publié: (2025)

MathlibPR: Pull Request Merge-Readiness Benchmark for Formal Mathematical Libraries
par: Xie, Zixuan, et autres
Publié: (2026)

Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning
par: Liu, Hui, et autres
Publié: (2024)

When Correct Demonstrations Hurt: Rethinking the Role of Exemplars in In-Context Learning
par: Qiu, Chenghao, et autres
Publié: (2026)

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
par: Ruoss, Anian, et autres
Publié: (2024)

Learning to Remember: End-to-End Training of Memory Agents for Long-Context Reasoning
par: Zhang, Kehao, et autres
Publié: (2026)