大模型推理能力

A principled analysis of Behavior Trees and their generalisations

Oliver Biggar, Mohammad Zamani, Iman Shames

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments 13 pages, 11 figures. The content of the previous version is now split between this and arXiv:2104.07919, which have both been significantly updated

Algorithmic Ethics: Formalization and Verification of Autonomous Vehicle Obligations

Colin Shea-Blymyer, Houssam Abbas

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments To be published in ACT Transactions on Cyber-Physical Systems Special Issue on Artificial Intelligence and Cyber-Physical Systems. arXiv admin note: text overlap with arXiv:2009.00738

Evidential Cyber Threat Hunting

Frederico Araujo, Dhilung Kirat, Xiaokui Shu, Teryl Taylor, Jiyong Jang

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments 5 pages, SDM AI4CS 2021

Journal ref In Proceedings of the 2021 SIAM AI/ML for Cybersecurity Workshop (AI4CS)

Artificial Intelligence: A Child's Play

Ravi Kashyap

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Journal ref Technological Forecasting and Social Change, 166, May 2021, 120555

Theory of Mind for Deep Reinforcement Learning in Hanabi

Andrew Fuchs, Michael Walton, Theresa Chadwick, Doug Lange

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Program Synthesis with Pragmatic Communication

Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments The second author and the third author contributed equally to this work

Formal Fields: A Framework to Automate Code Generation Across Domains

Jacques Basaldúa

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Online Handbook of Argumentation for AI: Volume 1

OHAAI Collaboration, Federico Castagna, Timotheus Kampik, Atefeh Keshavarzi Zafarghandi, Mickaël Lafages, Jack Mumford, Christos T. Rodosthenous, Samy Sá, Stefan Sarkadi, Joseph Singleton, Kenneth Skiba, Andreas Xydis

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments editor: Federico Castagna and Francesca Mosca and Jack Mumford and Stefan Sarkadi and Andreas Xydis

Machine Common Sense

Alexander Gavrilenko, Katerina Morozova

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Towards Concise, Machine-discovered Proofs of Gödel's Two Incompleteness Theorems

Elijah Malaby, Bradley Dragun, John Licato

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Journal ref In Proceedings of The 2020 International Florida Artificial Intelligence Research Society Conference (FLAIRS-33)

JS-son -- A Lean, Extensible JavaScript Agent Programming Library

Timotheus Kampik, Juan Carlos Nieves

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments Accepted for the post-proceedings of EMAS 2019

Towards A Logical Account of Epistemic Causality

Shakil M. Khan, Mikhail Soutchanski

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments In Proceedings CREST 2019, arXiv:1910.13641

Journal ref EPTCS 308, 2019, pp. 1-16

nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems

Chih-Hong Cheng, Chung-Hao Huang, Georg Nührenberg

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.LG

Comments Tool available at https://github.com/dependable-ai/nn-dependability-kit

Efficiently Checking Actual Causality with SAT Solving

Amjad Ibrahim, Simon Rehwald, Alexander Pretschner

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments 18 pages, In: Dependable Software Systems Engineering, p. to appear (2019)

Learning $\textit{Ex Nihilo}$

Selmer Bringsjord, Naveen Sundar Govindarajulu

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Situational Grounding within Multimodal Simulations

James Pustejovsky, Nikhil Krishnaswamy

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments AAAI-19 Workshop on Games and Simulations for Artificial Intelligence

"Dave...I can assure you...that it's going to be all right..." -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships

Brett W Israelsen, Nisar R Ahmed

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments final version of accepted manuscript

The informal semantics of Answer Set Programming: A Tarskian perspective

Marc Denecker, Yuliya Lierler, Miroslaw truszczynski, Joost Vennekens

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Argument-based Belief in Topological Structures

Chenwei Shi, Sonja Smets, Fernando R. Velázquez-Quesada

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments In Proceedings TARK 2017, arXiv:1707.08250

Journal ref EPTCS 251, 2017, pp. 489-503

A logical model of Theory of Mind for virtual agents in the context of job interview simulation

Marwen Belkaid, Nicolas Sabouret

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Knowledge-Based Programs as Plans: Succinctness and the Complexity of Plan Existence

Jerome Lang, Bruno Zanuttini

专题命中 代码与定理证明 ：planning(abstract)；分类 cs.AI

Comments 10 pages, Contributed talk at TARK 2013 (arXiv:1310.6382) http://www.tark.org

A Knowledge-based Treatment of Human-Automation Systems

Yoram Moses, Marcia K. Shamo

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments 39 pages, 1 figure

Probabilistic Models for Agents' Beliefs and Decisions

Brian Milch, Daphne Koller

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)

On the Formal Semantics of Speech-Act Based Communication in an Agent-Oriented Programming Language

R. H. Bordini, A. F. Moreira, R. Vieira, M. Wooldridge

专题命中 代码与定理证明 ：planning(abstract)；分类 cs.AI

Journal ref Journal Of Artificial Intelligence Research, Volume 29, pages 221-267, 2007

Measuring Intelligence through Games

Tom Schaul, Julian Togelius, Jürgen Schmidhuber

专题命中 代码与定理证明 ：planning(abstract)；分类 cs.AI

Compiling Causal Theories to Successor State Axioms and STRIPS-Like Systems

F. Lin

专题命中 代码与定理证明 ：planning(abstract)；分类 cs.AI

Journal ref Journal Of Artificial Intelligence Research, Volume 19, pages 279-314, 2003

Analysis Of Cancer Omics Data In A Semantic Web Framework

Matt Holford, James McCusker, Kei Cheung, Michael Krauthammer

专题命中 代码与定理证明 ：reasoning(abstract)；分类 cs.AI

Comments in Adrian Paschke, Albert Burger, Andrea Splendiani, M. Scott Marshall, Paolo Romano: Proceedings of the 3rd International Workshop on Semantic Web Applications and Tools for the Life Sciences, Berlin,Germany, December 8-10, 2010

Lark: Biologically Inspired Neuroevolution for Multi-Stakeholder LLM Agents

Lark：生物启发的多利益相关者大语言模型代理神经进化

Rikhil Tanugula, Dheeraj Chintapalli, Sunkalp Chandra

专题命中 代码与定理证明 ：reasoning(abstract,comments)

AI总结 Lark通过结合大语言模型推理与进化型多智能体系统，解决冗余与利益相关者权衡问题，采用四机制提升策略生成效率与透明度，实验显示其在30轮评估中表现优异且成本可控。

Comments 39th Conference on Neural Information Processing Systems (NeurIPS 2025) Workshop: NeurIPS 2025 Workshop on Efficient Reasoning

PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs

PAVE：基于前提的验证与编辑用于检索增强的大语言模型

Tianyi Huang, Caden Yang, Emily Yin, Eric Wang, Michael Zhang

机构 * Ryquo ； App-In Club 纠错

专题命中 代码与定理证明 ：分类 cs.CL、cs.AI；reasoning(comments)；logical reasoning(comments)

AI总结 PAVE通过在推理阶段验证和编辑检索到的证据，提高检索增强大语言模型的回答一致性。在两个证据基础问答任务中，PAVE在跨度基础基准上提升了32.7个准确率点。

Comments Accepted at the ICLR 2026 Workshop on Logical Reasoning of Large Language Models

KBSpec: LLM-driven Formal Specification Generation with Evolving Domain Knowledge Base

KBSpec：基于演化领域知识库的LLM驱动形式化规约生成

Wenhan Wang, Zeyu Sun

专题命中 代码与定理证明 ：verifier(abstract)

AI总结 提出KBSpec方法，利用外部官方文档和内部验证器反馈的双源知识增强LLM，通过自演化知识库持续更新成功轨迹，无需调参或标注数据，在JML规约生成上验证通过率提升10-25%。