大模型推理能力

Neuro Symbolic Knowledge Reasoning for Procedural Video Question Answering

用于过程视频问答的神经符号知识推理

Basura Fernando, Thanh-Son Nguyen, Hong Yang, Tzeh Yuan Neoh, Hao Zhang, Ee Yeo Keat

机构 * Centre for Frontier AI Research, A*STAR, Singapore（前沿人工智能研究所以（A*STAR）） ； Institute of High-Performance Computing, A*STAR, Singapore（高性能计算研究所（A*STAR）） ； College of Computing and Data Science, NTU, Singapore（计算与数据科学学院（NTU）） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出KML框架，通过神经符号方法提升过程视频问答的推理能力，结合知识图谱实现可解释的多步骤推理。

Comments This paper is under review at IEEE Transactions on Neural Networks and Learning Systems. Personal use is permitted, but republication/redistribution requires IEEE permission

Enhancing Vision Language Models with Logic Reasoning for Situational Awareness

通过逻辑推理增强视觉语言模型以提升情境感知能力

Pavana Pradeep, Krishna Kant, Suya Yu

机构 * CIS Department, Temple University（Temple大学计算机与信息科学系） ； ARL（美国陆军研究实验室） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文通过整合逻辑推理与传统计算机视觉方法，提升视觉语言模型在情境感知中的准确性与细粒度事件识别能力。

Comments Accepted for publication in IEEE Transactions on AI

Incentivizing Cardiologist-Like Reasoning in MLLMs for Interpretable Echocardiographic Diagnosis

激励MLLMs实现类似心内科医生的推理以实现可解释的超声心动图诊断

Yi Qin, Lehan Wang, Chenxu Zhao, Alex P. W. Lee, Xiaomeng Li

机构 * The Hong Kong University of Science and Technology（香港科学与技术大学） ； The Chinese University of Hong Kong（香港中文大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出CRT和CardiacMind，通过引入心内科医生的思维模式，提升MLLMs在超声心动图诊断中的推理能力，实现48%的诊断性能提升。

Video Evidence to Reasoning Efficient Video Understanding via Explicit Evidence Grounding

视频证据推理：通过显式证据接地实现高效的视频理解

Yanxiang Huang, Guohua Gao, Zhaoyang Wei, Jianyuan Ni

机构 * Department of Applied Mathematics, The Hong Kong Polytechnic University（应用数学系，香港理工大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出CoE框架，通过显式证据接地模块和强化学习优化的锚定协议，提升视频推理的准确性和可靠性。

Comments 6 pages

Journal ref ICME 2026

How Does a Virtual Agent Decide Where to Look? Symbolic Cognitive Reasoning for Embodied Head Rotation

虚拟代理如何决定看向何处？基于具身头部旋转的符号认知推理

Juyeong Hwang, Seong-Eun Hong, JaeYoung Seon, Hyeongyeop Kang

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出SCORE框架，通过符号认知推理实现具身头部旋转，结合视觉-语言模型和大语言模型，使虚拟代理能合理预测头部运动及背后动机。

Comments 13 pages, 8 figures. Accepted to SIGGRAPH Asia Conference Papers '25

Journal ref SIGGRAPH Asia Conference Papers '25, December 15-18, 2025, Hongkong

Argumentative Reasoning with Language Models on Non-factorized Case Bases

基于非因子化案例库的语言模型论证推理

Wachara Fungwacharakorn, May Myo Zin, Ha-Thanh Nguyen, Yuntao Kong, Ken Satoh

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出AAM-CBR框架，通过语言模型实现非因子化案例库的基于案例推理，提升灵活性和隐私性，并展示在因素数量增加时需结合符号推理以提高效果。

Comments Presented at NeLaMKRR@KR, 2025 (arXiv:2511.09575)

Looking Beyond Visible Cues: Implicit Video Question Answering via Dual-Clue Reasoning

超越可见线索：通过双线索推理进行隐式视频问答

Tieyuan Chen, Huabin Liu, Yi Wang, Chaofan Gan, Mingxi Lyu, Ziran Qin, Shijie Li, Liquan Shen, Junhui Hou, Zheng Wang, Weiyao Lin

机构 * Shanghai Jiao Tong University（上海交通大学） ； ZhongguanCun Academy（中关村学院） ； Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； Shanghai University（上海大学） ； City University of Hong Kong（香港城市大学） ； Wuhan University（武汉大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出隐式视频问答任务和IRM模型，通过双线索推理提升隐式问答性能，优于现有模型。

Comments Preprint

LockForge: Automating Paper-to-Code for Logic Locking with Multi-Agent Reasoning LLMs

LockForge: 基于多智能体推理LLM的逻辑锁纸到代码自动化

Akashdeep Saha, Zeng Wang, Prithwish Basu Roy, Johann Knechtel, Ozgur Sinanoglu, Ramesh Karri

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 LockForge通过多智能体推理LLM自动化将逻辑锁论文描述转换为可执行代码，解决可重复性难题，提供系统化验证框架和基准测试。

Reasoning Meets Representation: Envisioning Neuro-Symbolic Wireless Foundation Models

推理与表征的结合：展望神经符号无线基础模型

Jaron Fontaine, Mohammad Cheraghinia, John Strassner, Adnan Shahid, Eli De Poorter

专题命中 逻辑推理 ：reasoning(title,abstract)

AI总结 本文提出神经符号无线基础模型，结合神经网络与符号推理，以解决无线通信中的可解释性、鲁棒性和合规性问题，推动6G网络的智能化发展。

Comments Accepted at the 39th Conference on Neural Information Processing Systems (NeurIPS 2025) Workshop: AI and ML for Next-Generation Wireless Communications and Networking (AI4NextG)

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)

ReTrace: Interactive Visualizations for Reasoning Traces of Large Reasoning Models

Ludwig Felder, Jacob Miller, Markus Wallinger, Stephen Kobourov, Chunyang Chen

专题命中 逻辑推理 ：reasoning(title,abstract)

NeuS-QA: Grounding Long-Form Video Understanding in Temporal Logic and Neuro-Symbolic Reasoning

Sahil Shah, S P Sharan, Harsh Goel, Minkyu Choi, Mustafa Munir, Manvik Pasula, Radu Marculescu, Sandeep Chinchali

专题命中 逻辑推理 ：reasoning(title,abstract)

SAR-LM: Symbolic Audio Reasoning with Large Language Models

Termeh Taheri, Yinghao Ma, Emmanouil Benetos

机构 * School of Electronic Engineering（电子工程学院） ； Computer Science, Queen Mary University of London, London, United Kingdom（计算机科学，伦敦大学玛丽女王学院，伦敦，英国） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

Neuro-Symbolic Spatial Reasoning in Segmentation

Jiayi Lin, Jiabo Huang, Shaogang Gong

专题命中 逻辑推理 ：reasoning(title,abstract)

Graph-Fused Vision-Language-Action for Policy Reasoning in Multi-Arm Robotic Manipulation

Shunlei Li, Longsen Gao, Jiuwen Cao, Yingbai Hu

机构 * Machine Learning and I-health International Cooperation Base of Zhejiang Province, Artificial Intelligence Institute, Hangzhou Dianzi University, Zhejiang（浙江省机器学习与健康国际合作基地、人工智能学院、杭州电子大学） ； Electrical and Computer Engineering Department, The University of New Mexico（新墨西哥大学电气与计算机工程系） ； School of Computation, Information and Technology, Technical University of Munich（慕尼黑技术大学计算、信息与技术学院） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments This paper is submitted to IEEE IROS 2025 Workshop AIR4S

An Iterative Approach for Heterogeneous Multi-Agent Route Planning with Resource Transportation Uncertainty and Temporal Logic Goals

Gustavo A. Cardona, Kaier Liang, Cristian-Ioan Vasile

机构 * Mechanical Engineering and Mechanics Department（机械工程与力学系） 纠错

专题命中 逻辑推理 ：planning(title,abstract)

NAVER: A Neuro-Symbolic Compositional Automaton for Visual Grounding with Explicit Logic Reasoning

Zhixi Cai, Fucai Ke, Simindokht Jahangard, Maria Garcia de la Banda, Reza Haffari, Peter J. Stuckey, Hamid Rezatofighi

机构 * Monash University（莫纳什大学） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments ICCV 2025

Shadow Wireless Intelligence: Large Language Model-Driven Reasoning in Covert Communications

Yuanai Xie, Zhaozhi Liu, Xiao Zhang, Shihua Zhang, Rui Hou, Minrui Xu, Ruichen Zhang, Dusit Niyato

专题命中 逻辑推理 ：reasoning(title,abstract)

Changing the Rules of the Game: Reasoning about Dynamic Phenomena in Multi-Agent Systems

Rustam Galimullin, Maksim Gladyshev, Munyque Mittelmann, Nima Motamed

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments Extended version of the AAMAS 2025 paper of the same name. In this version, proof of Theorem 4.1 is corrected, and all new text is in blue. We want to thank Stéphane Demri for spotting the problem

Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Wang Lin, Liyu Jia, Wentao Hu, Kaihang Pan, Zhongqi Yue, Wei Zhao, Jingyuan Chen, Fei Wu, Hanwang Zhang

机构 * Zhejiang University（浙江大学） ； Nanyang Technological University（南洋理工大学） ； Huawei Singapore Research Center（华为新加坡研究中心） 纠错

专题命中 逻辑推理 ：reasoning(title,abstract)

PathVLM-R1: A Reinforcement Learning-Driven Reasoning Model for Pathology Visual-Language Tasks

Jianyu Wu, Hao Yang, Xinhua Zeng, Guibing He, Zhiyu Chen, Zihui Li, Xiaochuan Zhang, Yangyang Ma, Run Fang, Yang Liu

专题命中 逻辑推理 ：reasoning(title,abstract)

SCOOP: A Framework for Proactive Collaboration and Social Continual Learning through Natural Language Interaction andCausal Reasoning

Dimitri Ognibene, Sabrina Patania, Luca Annese, Cansu Koyuturk, Franca Garzotto, Giuseppe Vizzari, Azzurra Ruggeri, Simone Colombani

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments 5 pages

Logic Induced High-Order Reasoning Network for Event-Event Relation Extraction

Peixin Huang, Xiang Zhao, Minghao Hu, Zhen Tan, Weidong Xiao

专题命中 逻辑推理 ：reasoning(title,abstract)

Reasoning about Strategic Abilities in Stochastic Multi-agent Systems

Yedi Zhang, Fu Song, Taolue Chen, Xuzhi Wu

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments Correction required and the replacement version not available shortly

Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models

Yuchen Yang, Kwonjoon Lee, Behzad Dariush, Yinzhi Cao, Shao-Yuan Lo

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments Accepted at European Conference on Computer Vision (ECCV) 2024

Toward Programming Languages for Reasoning: Humans, Symbolic Systems, and AI Agents

Mark Marron

专题命中 逻辑推理 ：reasoning(title,abstract)

ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition

Sanjoy Kundu, Shubham Trehan, Sathyanarayanan N. Aakur

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments Extended abstract of arXiv:2305.16602 for CVPR EgoVis Workshop

Towards a Distributed Platform for Normative Reasoning and Value Alignment in Multi-Agent Systems

Miguel Garcia-Bohigues, Carmengelys Cordova, Joaquin Taverner, Javier Palanca, Elena del Val, Estefania Argente

专题命中 逻辑推理 ：reasoning(title,abstract)

Robots Can Feel: LLM-based Framework for Robot Ethical Reasoning

Artem Lykov, Miguel Altamirano Cabrera, Koffivi Fidèle Gbagbe, Dzmitry Tsetserukou

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments The paper is submitted to the IEEE conference

Discovering Novel Actions from Open World Egocentric Videos with Object-Grounded Visual Commonsense Reasoning

Sanjoy Kundu, Shubham Trehan, Sathyanarayanan N. Aakur

专题命中 逻辑推理 ：reasoning(title,abstract)

Comments 25 Pages, 4 figures, 3 tables