大模型推理能力

ARCHE: A Novel Task to Evaluate LLMs on Latent Reasoning Chain Extraction

Pengze Li, Jiaqi Liu, Junchi Yu, Lihao Liu, Mingyu Ding, Wanli Ouyang, Shixiang Tang, Xi Chen

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

Comments Accepted to AAAI 2026

Concept-RuleNet: Grounded Multi-Agent Neurosymbolic Reasoning in Vision Language Models

Sanchit Sinha, Guangzhi Xiong, Zhenghao He, Aidong Zhang

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

Comments AAAI 2026 (oral)

RAC3: Retrieval-Augmented Corner Case Comprehension for Autonomous Driving with Vision-Language Models

Yujin Wang, Quanfeng Liu, Jiaqi Fan, Jinlong Hong, Hongqing Chu, Mengjian Tian, Bingzhao Gao, Hong Chen

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

Comments Accepted by IEEE Transactions on Multimedia

SciAgent: A Unified Multi-Agent System for Generalistic Scientific Reasoning

Xuchen Li, Ruitao Wu, Xuanbo Liu, Xukai Wang, Jinbo Hu, Zhixin Bai, Bohan Zeng, Hao Liang, Leheng Chen, Mingrui Chen, Haitian Zhong, Xuanlin Yang, Xu-Yao Zhang, Liu Liu, Jia Li, Kaiqi Huang, Jiahao Xu, Haitao Mi, Wentao Zhang, Bin Dong

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

Comments 1. To ensure result rigor, the model outputs require further evaluation by human experts. 2. The results may affect our conclusions and methods, thus necessitating a more detailed review. 3. We anticipate subsequent revisions may be substantial, potentially involving major adjustments to the methodology. Given the uncertainty surrounding the revision process, we decide to request a withdrawal

High-level reasoning while low-level actuation in Cyber-Physical Systems: How efficient is it?

Burak Karaduman, Baris Tekin Tezel, Moharram Challenger

专题命中 逻辑推理 ：reasoning(title,abstract)

DR-Encoder: Encode Low-rank Gradients with Random Prior for Large Language Models Differentially Privately

Huiwen Wu, Deyi Zhang, Xiaohan Li, Xiaogang Xu, Jiafei Wu, Zhe Liu

机构 * Zhejiang Laboratory（浙江实验室） 纠错

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

Fault2Flow: An AlphaEvolve-Optimized Human-in-the-Loop Multi-Agent System for Fault-to-Workflow Automation

Yafang Wang, Yangjie Tian, Xiaoyu Shen, Gaoyang Zhang, Jiaze Sun, He Zhang, Ruohua Xu, Feng Zhao

机构 * ISILC, Victoria University（维多利亚大学ISILC） ； Kexin Melbourne AI Research Center（墨尔本凯欣人工智能研究中心） ； Eastern Institute of Technology（东部技术研究所） 纠错

专题命中 逻辑推理 ：reasoning(abstract)；分类 cs.AI

LLM-Assisted Formalization Enables Deterministic Detection of Statutory Inconsistency in the Internal Revenue Code

Borchuluun Yadamsuren, Steven Keith Platt, Miguel Diaz

专题命中 逻辑推理 ：reasoning(abstract)；分类 cs.AI

Comments 29 pages, 3 appendices with Prolog code and full codebase available at: https://github.com/borchuluun/section121-inconsistency-detection

CausalGuard: A Smart System for Detecting and Preventing False Information in Large Language Models

Piyushkumar Patel

机构 * Microsoft（微软） 纠错

专题命中 逻辑推理 ：reasoning(abstract)；分类 cs.AI

Two Agents, One Prompt, and Your Weight

Elchanan Mossel, Amnon Schreiber

专题命中 逻辑推理 ：reasoning(abstract)

Comments Typos corrected