Counterfactual Reasoning

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Counterfactual reasoning asks what would have happened if an action, event, or condition had been different, supporting causal explanation, prediction, and decision-making. Common approaches use structural causal models and intervention graphs, potential-outcome methods, counterfactual explanations and recourse, or executable world models that simulate changes over time. Applications range from clinical treatment and network diagnosis to robotics and language models, with evaluations using synthetic causal systems, physical-video benchmarks such as CLEVRER, and tests of tabular or multi-hop reasoning. A central challenge is that observational data may not identify counterfactual outcomes, while fluent model-generated explanations can still violate causal structure or temporal constraints.

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46 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

CST-Bench: Benchmarking Counterfactual Spatial Transition Reasoning with Causal Transition On-Policy Self-Distillation
Nov 5, 2026Ying Li, Yongle Cheng, Jing Li +2Spatial Reasoning Benchmarks Multimodal Spatial Reasoning
School of Artificial Intelligence and Computer Science, North China University of Technology, Beijing, China · School of Artificial Intelligence, Jilin University, Changchun, China · ReLER Lab, Zhejiang University, Hangzhou, China
Structured Machine Theory of Mind from Agent Trajectories
Nov 4, 2026Nigel F. Doering, Rahath Malladi, Arshia Sangwan +4Theory of Mind Cognitive Modeling
Halıcıoğlu School of Data Science and Computing, University of California San Diego · New York University · Department of Philosophy and School of Data Science, University of Virginia
Backtracking Direct, Indirect and Total Effects
Oct 20, 2026Jose M. PeñaCausal Effect Estimation Causal Mediation Analysis
STIMA, IDA, LiU
Compact but Moving: Intervention-Relevant Geometry in Recurrent World Models
Sep 18, 2026Yuming Chen, Yang LiuWorld Models World Model Learning
College of Intelligent Robotics and Advanced Manufacturing, Fudan University Shanghai, China
From Explanations to Interventions: Execution-Guided Counterfactual Synthesis in Temporal Graphs
Sep 10, 2026Minwoo Yu, Young-guk HaCounterfactual Explanations Causal Counterfactual Generation
Smart Computing Laboratory, Department of Computer Science & Engineering, Konkuk University, Seoul 05029, Republic of Korea
Modus Tollens and Counterfactuals and Counterfactual Reasoning Based on Three Types of Negation
Sep 7, 2026Zhenghua PanLogical Reasoning Counterfactual Reasoning
School of Science, Institute of Mathematics and Physics, Jiangnan University, Wuxi 214122, China
SeaCausal-FL: Federated Fuzzy Causal Learning for Maritime IoT Fault Diagnosis and Counterfactual Reasoning
Sep 5, 2026Yuhang Qiu, Haihan Zhu, Koteeswaran Seerangan +6Fault Diagnosis Industrial Fault Diagnosis
School of Science, Jimei University, Xiamen 361021, China · School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China · Department of Computer Science and Engineering, R. M. K. Engineering College (Autonomous), Kavaraipettai - 601206, Tamil Nadu, India +4
C $^{3}$ T: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees
Sep 2, 2026S M Rafiuddin, Atriya SenSentiment Analysis Counterfactual Reasoning
Department of Computer Science Oklahoma State University Stillwater, OK 74078, USA
SocialReasonBench: A Video-QA Benchmark for Social Reasoning with Counterfactual Narrative Videos
Aug 31, 2026Zheyu Huang, Zijing Shi, Haozhe Luo +4Video Question Answering Multimodal Reasoning
AAII, University of Technology Sydney · Northeastern University · Fudan University +1
The Illusion of $\textit{What If}$ : Evaluating the Breakdown of Counterfactual Reasoning in LLMs
Aug 28, 2026Yucheng Wang, Yuetian Du, Zhengyi Liu +8Counterfactual Reasoning in Language Models Counterfactual Reasoning
Zhejiang University · Alibaba Group · City University of Hong Kong
Causal Modelling of Support Interventions for Student Competency Assessment
Aug 25, 2026Francesca Mangili, Alessandro Antonucci, Rafael CabañasEducational Assessment Causal Intervention
IDSIA - SUPSI Scuola Universitaria Professionale della Svizzera italiana (SUPSI) Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA) Lugano, Switzerland · University of Almería Almería, Spain
DeCo-MIL: Debiased Counterfactual Reasoning for Long-Tailed Whole Slide Image Analysis
Aug 12, 2026Xiaoxiao Li, Xitong Ling, Jiawen Li +6Whole-Slide Image Analysis Long-Tailed Classification
Tsinghua University · The Chinese University of Hong Kong, Shenzhen
PhysMind: From Video to Executable Worlds for Training-Free Physical Reasoning
Aug 5, 2026Chen Yang, Shenxiang Zeng, Haoyang Zhao +6Counterfactual Reasoning Physical Reasoning in Video
1Tsinghua University · 2The University of Hong Kong
Orca: Neural Operators for Causal Reasoning in Continuous Time
Jul 30, 2026Gerrit Großmann, David A. Selby, Sebastian J. VollmerStructural Causal Models Causal Counterfactual Generation
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
An Explicit World Model Based on Data-First Ontology: DaoQL Multimodal Storage Validation and Counterfactual Reasoning Evaluation
Jul 19, 2026Zhanbo Li, Shifeng Wu, Xiangjin Meng +1LLM Grounding Counterfactual Reasoning in Language Models
Graduate Students, School of Mathematics and Statistics, Chongqing University · DaoQL Project Group · Guangzhou Polytechnic Normal University
CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps
Jul 12, 2026JungMin Yun, JuneHyoung Kwon, YoungBin KimMulti-Hop QA LLM Evaluation
Department of Artificial Intelligence, Chung-Ang University · Graduate School of Advanced Imaging Sciences, Multimedia and Film, Chung-Ang University
NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO
Jul 4, 2026Xinqi ZhangCounterfactual Evaluation Moral Reasoning in Language Models
Tsinghua University
Prediction Sets for Counterfactual Decisions: Coverage, Optimality, and Conformal Prediction
Jul 2, 2026Yurui Zheng, Ying JinSet Prediction Conformal Prediction
School of Mathematical Sciences, Peking University · Department of Statistics and Data Science, University of Pennsylvania
MindEdit-Bench: Benchmarking Object-Level Counterfactual Spatial Reasoning in VLMs from In-the-Wild Photos
Jul 1, 2026Leyuan Yu, Xiao Tang, Minghao Liu +6VLM Evaluation Spatial Reasoning Benchmarks
ZODA · Tongji University · Zhejiang University +1
Testing Frontier Large Language Models' Physics Literacy in Parallel Physical Worlds
Jun 30, 2026Dong ZhangLLM Evaluation Physical Reasoning
Einstein World Models
Jun 25, 2026Munachiso Samuel Nwadike, Zangir Iklassov, Ali Mekky +2LLM Tool Use Counterfactual Reasoning
MBZUAI · RIKEN AIP, Japan · Tohoku University
DeepSWIP: Quotient-WMC Counterfactuals for Neural Probabilistic Logic Programs
Jun 18, 2026Saimun Habib, Vaishak Belle, Fengxiang HeProbabilistic Logic Structural Causal Models
University of Edinburgh
PragReST: Self-Reinforcing Counterfactual Reasoning for Pragmatic Language Understanding
Jun 17, 2026Jihyung Park, Minchao Huang, Leqi Liu +1Pragmatic Reasoning in Language Models Counterfactual Reasoning in Language Models
The University of Texas at Austin
NetCause: Counterfactual Learning for Root Cause Analysis in Large-Scale Networks
Jun 11, 2026Fabien Chraim, Jian Zhang, Dominik Janzing +3Anomaly Localization Causal Inference
Amazon Web Services, Seattle, Washington, USA
WorldKernel: A World Model is the Coupling Kernel of Admissible Possible Worlds
Jun 9, 2026Fabio RovaiStructural Causal Models Causal World Models
Decoupling Thought from Speech: Knowledge-Grounded Counterfactual Reasoning for Resilient Multi-Agent Argumentation
Jun 9, 2026Jakub Masłowski, Jarosław A. ChudziakMulti-Agent Debate Computational Argumentation
Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland
Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA
Jun 8, 2026Zhou Du, Hamid Krim, Xiao Wu +3Causal Representation Learning Video Question Answering
Graduate School of Informatics, Nagoya University, Nagoya 464-8601, Japan · Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA · School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611730, China +1
CRAFT: A Unified Counterfactual Reasoning Framework for Tabular Question Answering and Fact Verification
Jun 5, 2026Chenshuo Pan, Yu Zhao, Jie Zhang +7Table QA Claim Verification
Xingchen AGI Lab,China Telecom Artificial Intelligence Technology (Beijing) Co., Ltd
Outsmarting the Chameleon: Counterfactual Decoupling for Tactical OOD Shifts in Live Streaming Risk Assessment
Jun 1, 2026Yiran Qiao, Jing Chen, Jiaqi Xu +3Distribution Shift Robustness Causal Representation Learning
Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · ByteDance China, Hangzhou, China · State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences +1
Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis
May 26, 2026Jianzhe Gao, Churan Wang, Weiyi Zhang +5Healthcare Medical Diagnosis

Nov 5, 2026J/K move · Enter open · S save

CST-Bench: Benchmarking Counterfactual Spatial Transition Reasoning with Causal Transition On-Policy Self-Distillation

Ying Li, Yongle Cheng, Jing Li, Xingquan Cai+1

School of Artificial Intelligence and Computer Science, North China University of Technology, Beijing, China · School of Artificial Intelligence, Jilin University, Changchun, China · ReLER Lab, Zhejiang University, Hangzhou, China

Spatial Reasoning Benchmarks Multimodal Spatial Reasoning Counterfactual Reasoning Causal Reasoning in Language Models

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Spatial reasoning is a fundamental capability of multimodal large language models (MLLMs), yet existing benchmarks mainly focus on static scene understanding. When objects are moved or swapped, models must infer not only spatial relations but also how interventions change the scene state. To address this problem, we introduce CST-Bench, a benchmark for counterfactual spatial reasoning. CST-Bench contains 7,082 examples covering 6 intervention types and 12 transformation operators, with dense causal annotations including intervention sources, affected relations, expected effects, invariant relations, and metric changes. We benchmark general-purpose MLLMs on CST-Bench and further compare post-training strategies on CST-Bench and standard spatial benchmarks. Results show that methods effective for ordinary spatial reasoning can still fail under counterfactual interventions. We further formulate counterfactual spatial reasoning as causal state-transition modeling and propose CT-OPSD, which uses CST-Bench annotations to guide a teacher model in learning counterfactual state transitions and causal reasoning chains. These chains are then distilled into a student model that reasons only from real observations. Overall, experiment results establish CST-Bench as a challenging benchmark and reusable supervision resource for counterfactual spatial reasoning. CT-OPSD further provides an initial demonstration of how its annotations can support model improvement.