大模型推理能力

Enhancing Logical Reasoning in Language Models via Symbolically-Guided Monte Carlo Process Supervision

Xingwei Tan, Marco Valentino, Mahmud Akhter, Maria Liakata, Nikolaos Aletras

机构 * School of Computer Science, University of Sheffield（谢菲尔德大学计算机科学学院） ； School of Electronic Engineering and Computer Science, Queen Mary University of London（伦敦大学玛丽女王学院电子工程与计算机科学学院） ； The Alan Turing Institute（艾伦·图灵研究所） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；planning(abstract)；分类 cs.CL

Comments EMNLP 2025 (Main), 9+6 pages

GreenMind: A Next-Generation Vietnamese Large Language Model for Structured and Logical Reasoning

Luu Quy Tung, Hoang Quoc Viet, Pham Bao Loc, Vo Trong Thu

机构 * John Von Neumann Institute（约翰·冯·诺依曼研究所） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title)；chain-of-thought(abstract)；CoT(abstract)

Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning

Hyun Ryu, Gyeongman Kim, Hyemin S. Lee, Eunho Yang

机构 * KAIST（韩国科学技术院） ； MIT（麻省理工学院） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；chain-of-thought(abstract)；分类 cs.CL

Comments ICLR 2025 camera-ready version

Journal ref The Thirteenth International Conference on Learning Representations (ICLR 2025)

Learning to Reason via Mixture-of-Thought for Logical Reasoning

Tong Zheng, Lichang Chen, Simeng Han, R. Thomas McCoy, Heng Huang

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；chain-of-thought(abstract)；分类 cs.CL

Comments 38 pages

Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation

Chengwen Qi, Ren Ma, Bowen Li, He Du, Binyuan Hui, Jinwang Wu, Yuanjun Laili, Conghui He

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title)；chain-of-thought(abstract)；CoT(abstract)

Comments Accepted by ICLR 2025

ARN: Analogical Reasoning on Narratives

Zhivar Sourati, Filip Ilievski, Pia Sommerauer, Yifan Jiang

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；chain-of-thought(abstract)；分类 cs.CL

CLR-Fact: Evaluating the Complex Logical Reasoning Capability of Large Language Models over Factual Knowledge

Tianshi Zheng, Jiaxin Bai, Yicheng Wang, Tianqing Fang, Yue Guo, Yauwai Yim, Yangqiu Song

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；chain-of-thought(abstract)；分类 cs.CL

Comments 9 pages

On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Sree Harsha Tanneru, Dan Ley, Chirag Agarwal, Himabindu Lakkaraju

专题命中 逻辑推理 ：reasoning(title,abstract)；chain-of-thought(title,abstract)；CoT(abstract)；分类 cs.CL

LogiGAN: Learning Logical Reasoning via Adversarial Pre-training

Xinyu Pi, Wanjun Zhong, Yan Gao, Nan Duan, Jian-Guang Lou

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；verifier(abstract)；分类 cs.CL

Comments Accepted by NeurIPS 2022

Response: Emergent analogical reasoning in large language models

Damian Hodel, Jevin West

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI

Comments Response to publication in Nature Human Behaviour titled "Emergent analogical reasoning in large language models," (Webb, Holyoak, and Lu, 2023, arXiv:2212.09196). 14 pages

Reason Popper-ly: Patching In-Context Reasoning with Inductive Logic Programming

合理地运用波普尔方法：用归纳逻辑编程修补上下文推理

Zirong Chen, Meiyi Ma

机构 * Vanderbilt University（范德堡大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；CoT(abstract,abstract_cn)；chain-of-thought(abstract)；verifier(abstract)

AI总结 研究针对思维链提示中间步骤逻辑不合理问题，提出Reason Popper-ly框架，用归纳逻辑编程学习规则作在线验证器校正步骤，在CLUTRR基准测试中提升了模型准确率，还产生细粒度错误分类法，优于完全外部符号管道。

Comments Accepted at the 20th Conference on Neurosymbolic Learning and Reasoning

Exploring the Reversal Curse and Other Deductive Logical Reasoning in BERT and GPT-Based Large Language Models

探索BERT和GPT类大语言模型中的反向诅咒及其他演绎逻辑推理

Da Wu, Jingye Yang, Kai Wang

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本研究发现BERT对反向诅咒免疫，而GPT在处理多集合逻辑推理时存在困难，揭示了两种模型在简单与复杂逻辑推理中的差异。

Comments Final revision. To appear in Patterns

SLR: Automated Synthesis for Scalable Logical Reasoning

SLR：可扩展逻辑推理中的自动化合成

Lukas Helff, Ahmad Omar, Felix Friedrich, Antonia Wüst, Hikaru Shindo, Rupert Mitchell, Tim Woydt, Patrick Schramowski, Wolfgang Stammer, Kristian Kersting

机构 * TU Darmstadt（图宾根大学） ； DFKI（德意志联邦防务学院） ； Meta FAIR ； CERTAIN, Germany（德国CERTAIN） ； Lab1141 ； MPI-Inf（马克斯·普朗克研究所） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 SLR通过可扩展逻辑推理系统自动化生成指令提示、验证程序和潜在真实规则，创建SLR-Bench基准测试，展示LLM在逻辑推理中的表现及课程学习提升效果。

RCoT-Seg: Reinforced Chain-of-Thought for Video Reasoning and Segmentation

RCoT-Seg：强化链式推理用于视频推理与分割

Junwei Wen, Deshui Miao, Guangming Lu, Xin Li, Wenjie Pei

机构 * Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳）） ； Pengcheng Laboratory（鹏城实验室） ； Pazhou Lab (Huangpu)（琶洲实验室（黄埔）） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；chain-of-thought(title)；CoT(abstract,abstract_cn)

AI总结 本文提出RCoT-Seg框架，通过分离时间推理与空间感知，改进视频分割中关键帧选择与定位，提升多目标场景下的鲁棒性与精度。

Comments 21 pages

MuSLR: Multimodal Symbolic Logical Reasoning

MuSLR：多模态符号逻辑推理

Jundong Xu, Hao Fei, Yuhui Zhang, Liangming Pan, Qijun Huang, Qian Liu, Preslav Nakov, Min-Yen Kan, William Yang Wang, Mong-Li Lee, Wynne Hsu

机构 * National University of Singapore（新加坡国立大学） ； Stanford University（斯坦福大学） ； Peking University（北京大学） ； UniMelb（墨尔本大学） ； University of Auckland（奥克兰大学） ； MBZUAI（穆斯林人工智能研究所） ； University of California, Santa Barbara（加州大学圣芭芭拉分校） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；chain-of-thought(abstract)

AI总结 MuSLR提出了一种多模态符号逻辑推理基准，通过形式逻辑规则提升VLMs的推理能力，显著提升链式推理性能及复杂逻辑处理效果。

Comments Accepted by NeurIPS 2025

Live-E2T: Real-time Threat Monitoring in Video via Deduplicated Event Reasoning and Chain-of-Thought

Yuhan Wang, Cheng Liu, Zihan Zhao, Weichao Wu

机构 * School of Mechatronical Engineering, Beijing Institute of Technology（机械工程学院，北京理工大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；chain-of-thought(title,abstract)；logical reasoning(abstract)

SATBench: Benchmarking LLMs' Logical Reasoning via Automated Puzzle Generation from SAT Formulas

Anjiang Wei, Yuheng Wu, Yingjia Wan, Tarun Suresh, Huanmi Tan, Zhanke Zhou, Sanmi Koyejo, Ke Wang, Alex Aiken

机构 * Stanford University（斯坦福大学） ； UCLA（加州大学洛杉矶分校） ； UIUC（伊利诺伊大学香槟分校） ； CMU（卡内基梅隆大学） ； Nanjing University（南京大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

A Comparative Study of Neurosymbolic AI Approaches to Interpretable Logical Reasoning

Michael K. Chen

机构 * Raffles Institution（拉夫斯学院） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to NeSy 2025

ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, Yejin Choi

机构 * Allen Institute for AI（艾伦人工智能研究所） ； University of Washington（华盛顿大学） ； Stanford University（斯坦福大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to ICML 2025

Enhancing Non-Core Language Instruction-Following in Speech LLMs via Semi-Implicit Cross-Lingual CoT Reasoning

Hongfei Xue, Yufeng Tang, Hexin Liu, Jun Zhang, Xuelong Geng, Lei Xie

机构 * Northwestern Polytechnical University（西北工业大学） ； ByteDance Inc.（字节跳动公司） ； Nanyang Technological University（南洋理工大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；CoT(title,abstract)；chain-of-thought(abstract)

Comments 10 pages, 6 figures, Submitted to ACM MM 2025

Evaluating the Robustness of Analogical Reasoning in Large Language Models

Martha Lewis, Melanie Mitchell

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 31 pages, 13 figures. arXiv admin note: text overlap with arXiv:2402.08955

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Xufeng Zhao, Mengdi Li, Wenhao Lu, Cornelius Weber, Jae Hee Lee, Kun Chu, Stefan Wermter

专题命中 逻辑推理 ：reasoning(title,abstract)；chain-of-thought(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted in COLING 2024. Code see https://github.com/xf-zhao/LoT

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Bin Lei, pei-Hung Lin, Chunhua Liao, Caiwen Ding

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

In-Context Analogical Reasoning with Pre-Trained Language Models

Xiaoyang Hu, Shane Storks, Richard L. Lewis, Joyce Chai

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning

Soumya Sanyal, Yichong Xu, Shuohang Wang, Ziyi Yang, Reid Pryzant, Wenhao Yu, Chenguang Zhu, Xiang Ren

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted at ACL 2023, code available at https://github.com/INK-USC/APOLLO

Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming

Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric Xing

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ACL 2023 Findings

Multimodal Analogical Reasoning over Knowledge Graphs

Ningyu Zhang, Lei Li, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted by ICLR 2023. The project website is https://zjunlp.github.io/project/MKG_Analogy/introduction.html

ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

Weihao Yu, Zihang Jiang, Yanfei Dong, Jiashi Feng

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ICLR 2020 paper. Project page: http://whyu.me/reclor/

Improving Symbolic Translation of Language Models for Logical Reasoning

提升语言模型的符号翻译以增强逻辑推理

Ramya Keerthy Thatikonda, Jiuzhou Han, Wray Buntine, Ehsan Shareghi

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.CL、cs.AI

AI总结 本文通过微调和增量推理框架，提升小型语言模型在逻辑推理中的符号翻译能力，减少错误率并提高推理性能。

Comments The Third workshop of NeusymBridge @AAAI 2026 (Bridging Neurons and Symbols for NLP and Knowledge Graph Reasoning)

Can Large Reasoning Models do Analogical Reasoning under Perceptual Uncertainty?

Giacomo Camposampiero, Michael Hersche, Roger Wattenhofer, Abu Sebastian, Abbas Rahimi

机构 * IBM Research - Zurich（IBM瑞士研究实验室） ； ETH Zürich（苏黎世联邦理工学院） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)；logical reasoning(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted at the 19th International Conference on Neural-Symbolic Learning and Reasoning (NeSy) 2025