UAI 2026

330 papers

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space

Long Minh Bui, Tuan Anh Le Van, Tung Phi Duc, Phi Le Nguyen, Jana Doppa

Causal Discovery with Metadata-Informed Latent Types

Philippe Brouillard, Alexandre Drouin, Dhanya Sridhar

Task Expansion and Cross Refinement for Open-World Conditional Modeling

Shreyas Bhat Brahmavar, Qiyang Liu, Yang Li, Junier Oliva

Bayesian Symbolic Regression with Entropic Reinforcement Learning

Oussama Boussif, Mohammed Mahfoud, Younesse Kaddar, Moksh Jain, Sida Li

Fundamental Limits and Optimal Methods for Sharp Analytical Causal Bounds in Instrumental Variable Models

Arefe Boushehrian, Mohammad Reza Badri, Sina Akbari, Negar Kiyavash

Pareto-Optimal Probabilistic Explanations: Balancing Cognitive Constraints and User Preferences

Louènas Bounia

Proximal Policy Optimization Suffices for On-Policy Reinforcement Learning

Rayane Bouftini, Mohammed Benzaouia

Characterising the Convergence of Imprecise Markov Chains

Jasper De Bock, Alexander Erreygers, Floris Persiau

Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem

Avrim Blum, Marten Garicano, Kavya Ravichandran, Dravyansh Sharma

Robust Weighted Triangulation of Causal Effects Under Model Uncertainty

Rohit Bhattacharya, Ina Ocelli, Ted Westling

Testing Partially-Identifiable Causal Queries Using Ternary Tests

Sourbh Bhadane, Joris M. Mooij, Philip Boeken, Onno Zoeter

Approximation Rates for Schrödinger Bridge Potentials via Fixed-Point ERM

Denis Belomestny, Alexey Naumov, Nikita Puchkin, Denis Suchkov

Bound to Disagree: Generalization Bounds via Certifiable Surrogates

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

Sparse recovery of Diffusion Dynamics: Handling High-Dimensionality in Repeated Short Trajectories

Elise Bayraktar, Charlotte Dion-Blanc

Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows

David Baumgartner, Eliezer de Souza da Silva, Inigo Urteaga

Gradual Uncertainty Refinement via Noise-Driven Curriculum: A Post-Hoc Meta-Model for Robust Uncertainty Quantification

Charmaine Barker, Daniel Bethell, Simos Gerasimou

Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalization

Vitória Barin-Pacela, Shruti Joshi, Isabela Camacho, Simon Lacoste-Julien, David Klindt

Dynamic Regret in Outlier-Oblivious Online Optimization using Nonconvex Robust Losses

Adarsh Barik, Anand Krishna, Vincent Y. F. Tan

Gaussian Process Limit Reveals Structural Benefits of Graph Transformers

Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar

Robust Transfer Learning With Side Information

Akram Awad, Shihab Ahmed, Yue Wang, George K. Atia

Probably Correct Optimal Stable Matching under Two-Sided Uncertainty

Andreas Athanasopoulos, Anne-Marie George, Christos Dimitrakakis

Certified Interventional Fidelity: Anytime-Valid, Adaptive Evaluation of Causal Claims in Mechanistic Interpretability

Amir Asiaee

Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment

Amir Asiaee, Samhita Pal

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions

Amir Asiaee, Kaveh Aryan, James P. Long

Workload-Preserving Differentially Private Synthetic Data for Causal Inference via Maximum-Entropy Calibration

Amir Asiaee, Kaveh Aryan

When and How Often is Weighted Majority Vote Optimal Under Log Loss?

Steven An, Sanjoy Dasgupta

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization

Theophilus Amaefuna, Hitesh Ulhas Vaidya, Anshuman Chhabra, Ankur Mali

PCU: Perturbation-Calibrated Uncertainty for Unsupervised Anomaly Detection

Mebarka Allaoui, Rachid Hedjam, Mohand Saïd Allili, Guoqiang Zhong

Contrastive Conformal Sets

Yahya Alkhatib, Wee Peng Tay

Distilling Safe LLM Systems via Soft Prompts for On Device Settings

Motasem Alfarra, Cristina Pinneri, Dana Kianfar, Mohammed Almousa, Christos Louizos