Machine Learning

Boosting with List-Decodable Codes COLT 2026 Bootstrapping Embeddings for Low Resource Languages EACL 2026 Bootstrapping LLMs via Preference-Based Policy Optimization AAAI 2026 Bootstrapping Personalized Insulin Therapy via Model-Based Reinforcement Learning: An In Silico Study AAAI 2026 BOP-Distrib: Revisiting 6D Pose Estimation Benchmarks for Better Evaluation under Visual Ambiguities WACV 2026 Bot Meets Shortcut: How Can LLMs Aid in Handling Unknown Invariance OOD Scenarios? AAAI 2026 Boundary-Aware LLM Augmentation for Low-Resource Event Argument Extraction EACL 2026 Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness UAI 2026 Bound to Disagree: Generalization Bounds via Certifiable Surrogates UAI 2026 BrainLMM: A Label-Free Framework for Mapping Multi-Semantic Representation in the Human Visual Cortex AAAI 2026 Branch, or Layer? Zeroth-Order Optimization for Continual Learning of Vision-Language Models AAAI 2026 BraSTORM: A Dual-Branch Self-Supervised Framework for EEG Representation Learning via Input-Level Spatio-Temporal Decomposition AAAI 2026 Breaking Alignment Barriers: TPS-Driven Semantic Correlation Learning for Alignment-Free RGB-T Salient Object Detection AAAI 2026 Breaking Bad: Component-Wise Parent Deletion for Score-Based Causal Discovery UAI 2026 Breaking Cross-View Associations: Byzantine Model Poisoning Attack against Vertical Federated Learning AAAI 2026 Breaking Down Market Barriers: Distilled Prompt-Tuning Approach for Cross-Market Recommendation AAAI 2026 Breaking Measurement Barriers: From Compressed Sensing to Deep Reconstruction AAAI 2026 Breaking Model Lock-in: Cost-Efficient Zero-Shot LLM Routing via a Universal Latent Space AAAI 2026 Breaking One-Size-Fits-All: Revisiting Out-of-Distribution Detection on Graphs Under Diverse Distribution Shifts AAAI 2026 Breaking Semantic Boundaries: Distribution-Guided Semantic Exploration for Creative Generation CVPR 2026 Breaking Task Boundaries: A Unified Model for 3D Medical Image Fusion and Segmentation Guided by Manifold Perspective AAAI 2026 Breaking the Adversarial Robustness-Performance Trade-off in Text Classification via Manifold Purification AAAI 2026 Breaking the Aggregation Bottleneck in Federated Recommendation: A Personalized Model Merging Approach AAAI 2026 Breaking the Dyadic Barrier: Rethinking Fairness in Link Prediction Beyond Demographic Parity AAAI 2026 Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection ACL 2026