Cover Image

Large Language Models Can Self-Improve in Long-context Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Siheng, Yang, Cheng, Cheng, Zesen, Liu, Lemao, Yu, Mo, Yang, Yujiu, Lam, Wai
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LLM2: Let Large Language Models Harness System 2 Reasoning
by: Yang, Cheng, et al.
Published: (2024)

A Survey on the Honesty of Large Language Models
by: Li, Siheng, et al.
Published: (2024)

TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild
by: Li, Huayang, et al.
Published: (2023)

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
by: Chung, Tsz Ting, et al.
Published: (2025)

CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
by: Gou, Zhibin, et al.
Published: (2023)

A Decomposition Perspective to Long-context Reasoning for LLMs
by: Xiao, Yanling, et al.
Published: (2026)

Vision-Language Models Can Self-Improve Reasoning via Reflection
by: Cheng, Kanzhi, et al.
Published: (2024)

Multi-LLM Collaborative Search for Complex Problem Solving
by: Yang, Sen, et al.
Published: (2025)

Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models
by: Huang, Liangjie, et al.
Published: (2025)

An Energy-based Model for Word-level AutoCompletion in Computer-aided Translation
by: Yang, Cheng, et al.
Published: (2024)

DepWiGNN: A Depth-wise Graph Neural Network for Multi-hop Spatial Reasoning in Text
by: Li, Shuaiyi, et al.
Published: (2023)

RePO: Replay-Enhanced Policy Optimization
by: Li, Siheng, et al.
Published: (2025)

Importance Weighting Can Help Large Language Models Self-Improve
by: Jiang, Chunyang, et al.
Published: (2024)

HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling
by: Zhou, Chulun, et al.
Published: (2025)

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

Can Large Language Models do Analytical Reasoning?
by: Hu, Yebowen, et al.
Published: (2024)

Improving Language Model Reasoning with Self-motivated Learning
by: Feng, Yunlong, et al.
Published: (2024)

TabularMath: Understanding Math Reasoning over Tables with Large Language Models
by: Tian, Shi-Yu, et al.
Published: (2025)

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

UloRL:An Ultra-Long Output Reinforcement Learning Approach for Advancing Large Language Models' Reasoning Abilities
by: Du, Dong, et al.
Published: (2025)

Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models
by: Qiu, Yifu, et al.
Published: (2025)

Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
by: Deng, Yang, et al.
Published: (2023)

CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
by: Wang, Zi-Han, et al.
Published: (2026)

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?
by: Wang, Jingyuan, et al.
Published: (2025)

Self-Discover: Large Language Models Self-Compose Reasoning Structures
by: Zhou, Pei, et al.
Published: (2024)

On the Worst Prompt Performance of Large Language Models
by: Cao, Bowen, et al.
Published: (2024)

Neuro-Symbolic Integration Brings Causal and Reliable Reasoning Proofs
by: Yang, Sen, et al.
Published: (2023)

CausalEval: Towards Better Causal Reasoning in Language Models
by: Yu, Longxuan, et al.
Published: (2024)

Language Models as Inductive Reasoners
by: Yang, Zonglin, et al.
Published: (2022)

Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models
by: Li, Xin, et al.
Published: (2024)

Advancing Large Language Model Attribution through Self-Improving
by: Huang, Lei, et al.
Published: (2024)

Agentic Reasoning for Large Language Models
by: Wei, Tianxin, et al.
Published: (2026)

LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models
by: Zhao, Liang, et al.
Published: (2024)

Break the Chain: Large Language Models Can be Shortcut Reasoners
by: Ding, Mengru, et al.
Published: (2024)

InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models
by: Yan, Yuchen, et al.
Published: (2025)

ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models
by: Zhang, Yuxiang, et al.
Published: (2024)

LongReasonArena: A Long Reasoning Benchmark for Large Language Models
by: Ding, Jiayu, et al.
Published: (2025)

Conditional Advantage Estimation for Reinforcement Learning in Large Reasoning Models
by: Chen, Guanxu, et al.
Published: (2025)

Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought
by: Lee, Jooyoung, et al.
Published: (2024)

ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning
by: Tang, Xiangru, et al.
Published: (2025)