Causal Reasoning in Language Models

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5 papers in the last four weeks, up 25% on the four weeks before. 0.0% of all new papers.

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From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning
Jun 10, 2026Haoping Yu, Yuanxi Li, Jing MaVisual Reasoning Causal Structure Learning
Department of Computer & Data Sciences, Case Western University, Cleveland, OH, US.
LLM Explainability with Counterfactual Chains and Causal Graphs
Jun 4, 2026Nirit Nussbaum-Hoffer, Nitay Calderon, Liat Ein-Dor +1LLM Reasoning with Graphs LLM Interpretability
Faculty of Data and Decision Sciences, Technion · IBM Research
Caliper: Probing Lexical Anchors versus Causal Structure in LLMs
Jun 3, 2026Zhenyu Yu, Shuigeng ZhouCausal Reasoning in Language Models Causal Reasoning
Fudan University
Multi-component Causal Tracing in Large Language Models
Jun 2, 2026Zirui Yan, Dennis Wei, Dmitriy A. Katz +2LLM Interpretability Causal Reasoning in Language Models
Rensselaer Polytechnic Institute · IBM Research
The Paradox of Outcome Optimization: A Causal Information-Theoretic Bound on Reasoning Shortcuts in LLMs
May 30, 2026Zihan Chen, Yiming Zhang, Wenxiang Geng +2Process Reward Models RL for Language Model Reasoning
1HFIPS, Chinese Academy of Sciences · University of Science and Technology of China
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
CausalFlip: A Benchmark for LLM Causal Judgment Beyond Semantic Matching
Feb 23, 2026Yuzhe Wang, Yaochen Zhu, Jundong LiLLM Evaluation Causal Reasoning in Language Models
University of Virginia Charlottesville, Virginia, USA
CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs
Apr 9, 2024Yu Zhou, Xingyu Wu, Jibin Wu +2LLM Evaluation Causal Discovery
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China · College of Computer Science, Chongqing University, Chongqing 400044, China

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From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning

Haoping Yu, Yuanxi Li, Jing Ma

Department of Computer & Data Sciences, Case Western University, Cleveland, OH, US.

Visual Reasoning Causal Structure Learning Causal Reasoning in Language Models VLM Reasoning

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Visual causal reasoning is essential for understanding and intervening in the physical world, requiring identification of causal variables from visual inputs and reasoning over intervention effects. Despite recent progress, large vision--language models (VLMs) remain brittle at such tasks, especially for interventional and counterfactual queries over multi-image inputs. Most existing explorations inject causal knowledge via textual prompts, leaving causal mechanisms external to model execution and limiting reliable control during inference. To address this problem, we propose BridgeVLM, which internalizes visual causal reasoning by inducing a causal graph from multi-image inputs and converting it into structured Causal Tokens executed by RAMP layers injected into the LLM decoder for causal message passing. We further introduce a unified training interface M3S for fine-grained causal supervision from different granularities (local/global level). BridgeVLM achieves 54.4% accuracy on intervention tasks on CausalVLBench (vs. 33.2% with prompt-level supervision), improves results on Causal3D from 43.6% to 49.0%, and substantially improves causal structure learning on CausalVLBench (

F_1

: 33.4%

\rightarrow

75.1%).

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