Partial Identification

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6 papers in the last four weeks, up 100% on the four weeks before. 0.1% of all new papers.

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Same Predictions, Different Harms: Causal Auditing of Patient World Models
Oct 4, 2026Yicheng Qi, Xiyi XiongStructural Causal Models Causal World Models
Imperial College London, London, United Kingdom
Path-specific harm decomposition: A partial identification framework
Sep 24, 2026Ruizi Yan, Dennis Frauen, Maresa Schröder +1Causal Effect Estimation Causal Mediation Analysis
Department of Statistics, University of Oxford · LMU Munich · Munich Center for Machine Learning (MCML)
The Delegation Blind Spot: Auditing Product Decisions from Agent Choices
Sep 22, 2026Shivam GuptaAI Agent Auditing Partial Identification
Independent Research
Information Set Emulation: Causal Certificates for AI Derived EHR Features
Sep 15, 2026Takes Fujita, Nobutaka HattoriCausal Effect Estimation Partial Identification
VRI · Department of Neurology, Juntendo University School of Medicine
The Anatomy and Boundary of Adaptation under Temporal Tabular Shift
Sep 14, 2026Tianyu Wang, Xi Vincent Wang, Lihui Wang +2Tabular Foundation Models Distribution Shift
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden · Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai, China
What Fixed-Rollout pass@k Evaluations Can Identify
Sep 10, 2026Pranav Singh, Prashant SinghConfidence Region Estimation Partial Identification
Department of Mathematics Indian Institute of Technology Ropar Ropar, Punjab 140001, India
Resolution-Aware Experimental Design under Partial Identifiability
Sep 3, 2026Sofianos Panagiotis FotiasPartial Identification Bayesian Experimental Design
National Technical University of Athens
Agent Behavioral Contracts II: Certifying Compositional Reliability Without Assuming Independence
Aug 13, 2026Varun Pratap Bhardwaj, Garima Singh, Arun Pratap BhardwajAgent Failure Analysis AI Agent Reliability
Qualixar / Independent Researcher, India · Independent Researcher, India
General Probabilities of Causation with Causal Knowledge
Aug 12, 2026Xin Shu, Zhen Lei, Ang LiPartial Identification Causal Identifiability
Department of Computer Science, Florida State University
Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness
Jul 23, 2026Jonathan Zhang, Erik Skalnes, Jacob Chen +1AI-Assisted Decision Making Causal Effect Estimation
Computer Science Dept., Johns Hopkins University, Baltimore, Maryland, USA
Partial Identification with Multiple Nonlinear Measurements of a Latent Regressor
Jul 13, 2026Burhan Ogut, Michelle YinPartial Identification Linear Regression
American Institutes for Research. · Northwestern University, School of Education and Social Policy.
NL-PAC: Specification Ambiguity and Certified Minimax Risk Floors in LLM-Mediated Supervision
Jul 9, 2026Berkay AnahtarciLLM Evaluation Partial Identification
Department of Mathematical Engineering, Özyeğin University, Istanbul, Türkiye
Root Cause Analysis with Latent Confounders using Partial Ancestral Graphs
Jun 18, 2026Henrique O. Caetano, Rafael Arone, Carlos Dias MacielPartial Identification Causal Inference
Signal Processing Laboratory, São Carlos School of Engineering, University of São Paulo, São Paulo, Brazil · Guaratinguetá School of Engineering, São Paulo State University, Guaratinguetá, Brazil
Identification and Inference for Algorithmic Frontiers with Selective Labels
Jun 12, 2026Yiqi Liu, Francesca Molinari, Amilcar VelezDebiased ML Parameter Identifiability
Department of Economics, Cornell University
Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss
Jun 2, 2026Prashant Shekhar, Caroline HowardOnline Advertising Partial Identification
Department of Mathematics Embry-Riddle Aeronautical University Daytona Beach, FL, USA
IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning
May 13, 2026Vahid Balazadeh, Hamidreza Kamkari, Medha Barath +2Causal Effect Estimation Parameter Identifiability
University of Toronto · Vector Institute · MIT CSAIL +1
Decision Support for Marketplace Policies under Incomplete Evidence: From Replay to Launch Readiness
May 13, 2026Prashant Shekhar, Caroline HowardAI-Assisted Decision Making Off-Policy Evaluation
Department of Mathematics Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
Identified-Set Geometry of Distributional Model Extraction under Top- $K$ Censored API Access
May 11, 2026Wenhua Nie, ZiCheng Zhu, Jianan Wu +3Parameter Identifiability Partial Identification
National Taiwan University
Optimal Experiments for Partial Causal Effect Identification
May 7, 2026Tobias Maringgele, Jalal EtesamiCausal Effect Estimation Partial Identification
Technical University of Munich · UC Berkeley
Uncertainty-aware Causal Decision Making via Effect Bound Decomposition
Jan 30, 2026Md Musfiqur Rahman, Ziwei Jiang, Hilaf Hasson +1Causal Effect Estimation Parameter Identifiability
Electrical and Computer Engineering, Purdue University · Computer Science, Johns Hopkins University · Cohesity

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Same Predictions, Different Harms: Causal Auditing of Patient World Models

Yicheng Qi, Xiyi Xiong

Imperial College London, London, United Kingdom

Structural Causal Models Causal World Models Partial Identification

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Patient world models used for clinical trial simulation can agree on transition kernels and arm-specific risks, yet disagree on the fraction of patients harmed by switching treatment---the counterfactual quantity that matters for intervention-aware reasoning. We audit this reliability gap in a two-stage shared-response SCM: a categorical intermediate health state is followed by common terminal care. Under independent stages, the sharp harm interval has closed-form endpoints for at most three intermediate states, with an exactness boundary at four states. Declared dependence and response-mismatch budgets yield calibrated outer bounds when stage independence or complete mediation is relaxed; in a symmetric three-state model the entire sensitivity frontier is sharp,

[0,\min\{1/2,1/3+(ρ+δ)/2\}]

, and shows exactly how budgets erase the gain over endpoint-only bounds. Two eight-variable response LPs propagate interventional uncertainty for finite-sample audits. Exact witnesses verify attainability. On public clinical simulators (EpiCare; sepsis), native configurations show little resolved stage dependence and no additional joint-compatibility gain over pairwise transport---honest negative results for reliability claims. All experiments are locally reproducible; guarantees remain conditional on the stated causal model. The results provide a concrete protocol for deciding when a patient world model is safe to trust for counterfactual harm.

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