Accepted papers

Causal Proxy Models for Concept-Based Model Explanations

Zhengxuan Wu, Karel D'Oosterlinck, Atticus Geiger, Amir Zur, Christopher Potts

Counterfactual Memorization in Neural Language Models

Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramer, Nicholas Carlini

Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility

Jacqueline Hoellig, Aniek Markus, Jef de Slegte, Prachi Bagave

In the Eye of the Beholder: Robust Prediction with Causal User Modeling

Amir Feder, Nir Rosenfeld

Time-uniform confidence bands for the CDF under nonstationarity

Paul Mineiro, Steve Howard

Rethinking Counterfactual Explanations as Local and Regional Counterfactual Policies

Salim I. Amoukou, Nicolas Brunel

Counterfactual Generation with Identifiability Guarantees

hanqi yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric Xing, Yulan He, Kun Zhang

Bayesian Predictive Synthetic Control Methods

Akira Fukuda, Masahiro Kato, Kenichiro McAlinn, Kosaku Takanashi

Causal Inference with Synthetic Control Methods by Density Matching under Implicit Endogeneitiy

Masahiro Kato, Akari Ohda, Masaaki Imaizumi, Kenichiro McAlinn

Why Don’t We Focus on Episodic Future Reasoning, Not Only Counterfactual?

Dongsu Lee, Minhae Kwon

Identification of Nonlinear Latent Hierarchical Causal Models

Lingjing Kong, Biwei Huang, Feng Xie, Eric Xing, Yuejie Chi, Kun Zhang

Counterfactuals for the Future

Lucius E.J. Bynum, Joshua Loftus, Julia Stoyanovich

Causal Dependence Plots

Joshua Loftus, Lucius E.J. Bynum, Sakina Hansen

Finding Counterfactually Optimal Action Sequences in Continuous State Spaces

Stratis Tsirtsis, Manuel Gomez Rodriguez

Empowering Counterfactual Reasoning for Graph Neural Networks via Inductivity

Samidha Verma, Burouj Armgaan, Sourav Medya, Sayan Ranu

Interventional and Counterfactual Inference with Diffusion Models

Patrick Chao, Patrick Blöbaum, Shiva Kasiviswanathan

Observational Counterfactual Explanations in Sequential Decision Making

Abdirisak Mohamed

Advancing Counterfactual Inference through Quantile Regression

Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang

Closed-loop Reasoning about Counterfactuals to Improve Policy Transparency

Michael Lee, Henny Admoni, Reid Simmons

Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ

Eoin D Delaney, Arjun Pakrashi, Derek Greene, Mark T Keane

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding

Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Ratsch, Tennenholtz Guy

Adaptive Principal Component Regression with Applications to Panel Data

Anish Agarwal, Keegan Harris, Justin Whitehouse, Steven Wu

Natural Counterfactuals With Necessary Backtracking

Guang-Yuan Hao, Jiji Zhang, Hao Wang, Kun Zhang

Strategyproof Decision-Making in Panel Data Settings and Beyond

Keegan Harris, Anish Agarwal, Chara Podimata, Steven Wu

Counterfactuals for Subjective Wellbeing Panel Data: Integrated Application of Statistical Ensemble and Machine Learning Methods

Jerry Chen, Li Wan

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing

Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

Counterfactual Explanation Policies in RL

Shripad V Deshmukh, Srivatsan R, Supriti Vijay, Jayakumar Subramanian, Chirag Agarwal

Leveraging Contextual Counterfactuals Toward Belief Calibration

Richard Zhang, Mike Lee, Sherol Chen

Extending counterfactual reasoning models to capture unconstrained social explanations

Stephanie Droop, Neil Bramley

Budgeting Counterfactual for Offline RL

Yao Liu, Pratik Chaudhari, Rasool Fakoor

Counterfactual Learning to Rank via Knowledge Distillation

Ehsan Ebrahimzadeh, Alex Cozzi, Abraham Bagherjeiran

Unveiling the Betrayal of Counterfactual Explanations within Recommender Systems

Ziheng Chen, Jin Huang, Ping Chang Lee, Fabrizio Silvestri, Hongshik Ahn, Jia  Wang, Yongfeng Zhang, Gabriele Tolomei

Counterfactually Comparing Abstaining Classifiers

Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas

Forward-INF : Efficient Data Influence Estimation with Duality-based Counterfactual Analysis

Myeongseob Ko, Feiyang Kang, Weiyan Shi, Ming Jin, Zhou Yu, Ruoxi Jia

Inverse Transition Learning for Characterizing Near-Optimal Dynamics in Offline Reinforcement Learning

Leo Benac, Sonali Parbhoo, Finale Doshi-Velez

Leveraging Factored Action Spaces for Off-Policy Evaluation

Aaman P Rebello, Shengpu Tang, Jenna Wiens, Sonali Parbhoo

Neuro-Symbolic Models of Human Moral Judgment: LLMs as Automatic Feature Extractors

joseph kwon, Sydney Levine, Joshua Tenenbaum

Navigating Explanatory Multiverse Through Counterfactual Path Geometry

Edward A Small, Yueqing Xuan, Kacper Sokol