Machine Learning

On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback ICML 2025 On Model Identification and Out-of-Sample Prediction of PCR with Applications to Synthetic Controls JMLR 2025 On Multilingual Encoder Language Model Compression for Low-Resource Languages IJCNLP 2025 On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches WACV 2025 On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes JMLR 2025 On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems AAAI 2025 On-Policy Algorithms for Continual Reinforcement Learning (Student Abstract) AAAI 2025 On-Policy Self-Alignment with Fine-grained Knowledge Feedback for Hallucination Mitigation ACL 2025 On Preference-based Stochastic Linear Contextual Bandits with Knapsacks AISTATS 2025 On Probabilistic Embeddings in Optimal Dimension Reduction JMLR 2025 On Probabilistic Truncation in Privacy-preserving Machine Learning AAAI 2025 On Pruning State-Space LLMs EMNLP 2025 On Quantizing Neural Representation for Variable-Rate Video Coding ICLR 2025 On Reference (In-)Determinacy in Natural Language Inference NAACL 2025 On Relation-Specific Neurons in Large Language Models EMNLP 2025 On Rollouts in Model-Based Reinforcement Learning ICLR 2025 On Scaling Up 3D Gaussian Splatting Training ICLR 2025 On Shallow Planning Under Partial Observability AAAI 2025 On Speeding Up Language Model Evaluation ICLR 2025 On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime ICLR 2025 On Support Samples of Next Word Prediction ACL 2025 On Synthesizing Data for Context Attribution in Question Answering ACL 2025 On Synthetic Data Strategies for Domain-Specific Generative Retrieval ACL 2025 On Teacher Hacking in Language Model Distillation ICML 2025 On Temperature Scaling and Conformal Prediction of Deep Classifiers ICML 2025