Causal Reasoning in Language Models

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The field asks whether language models can go beyond patterns of correlation to identify causes, predict what would happen under interventions, and reason about what might have happened otherwise. Researchers test these abilities with causal graphs, counterfactual questions, context-sensitive tasks in areas such as medicine and policy, and interactive settings where models must choose experiments. Approaches include prompting with explicit graphs, retrieval and tool use, multi-agent experiment design, and training with simulated interventions or step-level feedback. Models can handle some familiar causal patterns, but often confuse association with cause, miss context changes, or give fluent answers unsupported by a valid causal path; a central challenge is distinguishing genuine causal competence from shortcuts in language or benchmark performance.

Latest papers

102 papers13 papers in the last four weeks, up 30% on the four weeks before. 0.1% of all new papers.

Causal Interventions on Continuous Variables: A Case Study on Verb Bias in Steering Vectors for In-Context Learning
May 28, 2026Zhenghao Herbert Zhou, R. Thomas McCoy, Robert FrankLanguage Model Steering Causal Reasoning in Language Models
Department of Linguistics Yale University New Haven, CT 06511, USA
The Abstraction Gap in Vision-Language Causal Reasoning
May 27, 2026Chinh Hoang, Mohammad Rashedul HasanVLM Evaluation Causal Reasoning in Language Models
Department of Electrical and Computer Engineering, University of Nebraska–Lincoln, Lincoln, Nebraska, USA.
Why LLMs Fail at Causal Discovery and How Interventional Agents Escape
May 26, 2026Amartya Roy, Sonali ParbhooCausal Discovery Causal Reasoning in Language Models
SIRE, IIT Delhi and Robert Bosch GmbH, India · Imperial College London
CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists
May 25, 2026Junlin Yang, Dylan Zhang, Xiangchen Song +7Structural Causal Models LLM Agent Evaluation
Tsinghua University · University of Illinois Urbana-Champaign · Carnegie Mellon University +2
Causal Tongue-Tie: LLMs Can Encode Causal Direction, But Their Yes/No Outputs Fail to Express
May 25, 2026Ziyi Ding, Xiao-Ping ZhangLLM Evaluation Causal Reasoning in Language Models
Tsinghua Shenzhen International Graduate School, Tsinghua University Shenzhen, China
Towards a Universal Causal Reasoner
May 24, 2026Qirun Dai, Xiao Liu, Jiawei Zhang +3Causal Reasoning in Language Models Causal Reasoning
1The University of Chicago · University of Illinois Urbana-Champaign
From Correlation to Cause: A Five-Stage Methodology for Feature Analysis in Transformer Language Models
May 21, 2026Caleb MunigetyTransformer Interpretability Causal Reasoning in Language Models
Independent Researcher
MixRea: Benchmarking Explicit-Implicit Reasoning in Large Language Models
May 19, 2026Yuanqing Cai, Ziyi Huang, Minhao Liu +3LLM Evaluation LLM Prompting
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China
CasualSynth: Generating Structurally Sound Synthetic Data
May 17, 2026Zehua Cheng, Wei Dai, Jiahao Sun +1Structural Causal Models Synthetic Data Generation
Department of Computer Science, University of Oxford · FLock.io United Kingdom · Institute of Logic and Computation, TU Wien
Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform
May 13, 2026Feisal Alaswad, Batoul Aljaddouh, Maher Alrahhal +2Latent Dynamics Modeling Long-Horizon Agent Evaluation
Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur 603203, Tamil Nadu, India · Bio-Sensing and Bio-Sensors Group Smart Automation and Communication Technologies Research Institute of Sciences and Engineering University of Sharjah, UAE · Department of Computer Engineering College of Computing and Informatics University of Sharjah, UAE
CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models
May 13, 2026Armin Toroghi, Faeze Moradi Kalarde, Scott SannerAbductive Reasoning Causal Reasoning in Language Models
University of Toronto · Toronto, ON, Canada
PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models
May 13, 2026Sridhar MahadevanCausal World Models Causal Attribution
Adobe Research · University of Massachusetts, Amherst
CauSim: Scaling Causal Reasoning with Increasingly Complex Causal Simulators
May 9, 2026Nicolás Astorga, Anita Kriz, Mihaela van der SchaarStructural Causal Models Knowledge Augmentation for Language Models
DAMTP, University of Cambridge, Cambridge, UK
NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise
May 5, 2026Zhi Xu, Yun FuStructural Causal Models Causal Reasoning in Language Models
Northeastern University
SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification
May 5, 2026Zhifeng Hao, Zhongjie Chen, Junhao Lu +5Causal Reasoning in Language Models Causal Reasoning
School of Computer Science, Guangdong University of Technology · College of Mathematics and Computer, Shantou University · Huawei Noah’s Ark Lab +1
Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models
Apr 30, 2026Shubham Kumar, Narendra AhujaLLM Interpretability Causal Reasoning in Language Models
University of Illinois Urbana-Champaign
Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer
Apr 27, 2026Liangru Xiang, Yuxi Ma, Zhihao Cao +2LLM Grounding Causal Structure Learning
Department of Automation, Tsinghua University · State Key Laboratory of General Artificial Intelligence · Institute for Artificial Intelligence, Peking University +2
DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining
Apr 24, 2026Youze Zheng, Jianyou Wang, Yuhan Chen +8LLM Fine-Tuning Counterfactual Reasoning in Language Models
Laboratory for Emerging Intelligence, University of California, San Diego · University of Chicago · Elsevier +1
Implicit Causal Graph Construction in Text via Chain Discovery
Apr 20, 2026Liesbeth Allein, Marie-Francine MoensCausal Discovery Causal Reasoning in Language Models
Department of Computer Science, KU Leuven, Belgium · Department of Electronics and Information Systems, Ghent University, Belgium
CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification
Apr 16, 2026Yian Wang, Yuen Chen, Agam Goyal +1Causal Reasoning in Language Models LLM Safety
Department of Computer Science University of Illinois, Urbana-Champaign Champaign, IL 61801
Generating Effective CoT Traces for Mitigating Causal Hallucination
Apr 14, 2026Yiheng Zhao, Jun YanLLM Hallucination Mitigation Hallucination in Language Models
Concordia University, Montreal, Canada
InsightFlow: LLM-Driven Synthesis of Patient Narratives for Mental Health into Causal Models
Apr 14, 2026Shreya Gupta, Prottay Kumar Adhikary, Bhavyaa Dave +3Clinical Reasoning Mental Health
Department of Mathematics, IIT Delhi, Delhi, India · Department of Electrical Engineering, IIT Delhi, Delhi, India · Department of Computer Science and Engineering, IIIT Manipur, India
METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models
Apr 13, 2026Pengfeng Li, Chen Huang, Chaoqun Hao +4Causal Reasoning in Language Models LLM Evaluation
College of Computer Science, Sichuan University · Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education, China · Institute of Data Science, National University of Singapore
Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction
Apr 12, 2026Beicheng Bei, Hannah Hyesun Chun, Chen Guo +1Language Model Probing Representation Geometry in Language Models
Department of Linguistics, University of Rochester, 503 Lattimore Hall, Rochester, NY 14627
Thinking Fast, Thinking Wrong: Intuitiveness Modulates LLM Counterfactual Reasoning in Policy Evaluation
Apr 12, 2026Yanjie HeCounterfactual Reasoning in Language Models Causal Reasoning in Language Models
Independent Researcher
CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
Apr 12, 2026Elahe Khatibi, Ziyu Wang, Ankita Sharma +4Electrocardiogram Classification Causal Reasoning in Language Models
University of California, Irvine; Irvine, California, United States · Arizona State University; Tempe, Arizona, United States · California State University, Dominguez Hills; Carson, California, United States
MemCoT: Test-Time Scaling through Memory-Driven Chain-of-Thought
Apr 9, 2026Haodong Lei, Junming Liu, Yirong Chen +2Long-Context Reasoning in Language Models Memory-Augmented Language Models
Southeast University Nanjing, Jiangsu, China · Shanghai Artificial Intelligence Laboratory Shanghai, China
Debiasing Large Language Models toward Social Factors in Online Behavior Analytics through Prompt Knowledge Tuning
Mar 28, 2026Hossein Salemi, Jitin Krishnan, Hemant PurohitLanguage Model Debiasing Social Bias in Language Models
George Mason University, Fairfax, Virginia, United States
When Models Learn to Ask Why: Adaptive Causal Reasoning for Trustworthy Medical Vision-Language Models
Mar 24, 2026Jianxin Lin, Chunzheng Zhu, Peter J. Kneuertz +2Medical VLMs Causal Reasoning in Language Models
The Ohio State University · Hunan University · Amazon
SemEval-2026 Task 12: Abductive Event Reasoning: Towards Real-World Event Causal Inference for Large Language Models
Mar 23, 2026Pengfei Cao, Mingxuan Yang, Yubo Chen +4Abductive Reasoning Causal Reasoning in Language Models
The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China

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Causal Interventions on Continuous Variables: A Case Study on Verb Bias in Steering Vectors for In-Context Learning

Zhenghao Herbert Zhou, R. Thomas McCoy, Robert Frank

Department of Linguistics Yale University New Haven, CT 06511, USA

Language Model Steering Causal Reasoning in Language Models Causal Interventions in Language Models Causal Intervention

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Causal interventions in language model representations have largely targeted discrete features, like grammatical number. However, language models must also make use of features that are graded. We introduce a method for causal intervention on continuous variables: given activation vectors paired with a graded target variable, we localize a low-dimensional direction for that variable and use this direction to edit a vectors toward counterfactual target values. We apply this method to a continuous feature that is well-studied in psycholinguistics, namely verb bias (which reflects which syntactic structures tend to follow a given verb). We show that verb bias is causally represented in steering vectors extracted from large language models: counterfactual edits to verb bias systematically shift downstream structural preferences. Verb bias has also previously been linked to in-context learning; in further analyses, we find that steering vectors encode error signals that could drive the error-driven update behavior seen in in-context learning but that these aspects of the steering vectors are not causally used in downstream production. Overall, these results show causal interventions can be applied to continuous variables, though connecting continuous variables to in-context learning remains a challenge.