Machine Learning

Think Then Rewrite: Reasoning Enhanced Query Rewriting for Domain Specific Retrieval AAAI 2026 Think Wise, Collaborate Effectively: A Rationale-Aware LLM-Based Recommender with Reinforcement Learning from Collaborative Signals AAAI 2026 Three Types of Calibration using Properties and their Semantic and Formal Relationships JMLR 2026 TiCLS: Tightly Coupled Language Text Spotter WACV 2026 Tifin India at SemEval-2026 Task 5: Semantic Bridge: Augmented Encoding for Word Sense Plausibility SemEval 2026 Tight Bounds for Logistic Regression with Large Stepsize Gradient Descent in Low Dimension COLT 2026 Tighter Truncated Rectangular Prism Approximation for RNN Robustness Verification AAAI 2026 Tight list replicability bounds via a novel sphere covering theorem COLT 2026 Tight Long-Term Tail Decay of (Clipped) SGD in Non-Convex Optimization COLT 2026 Tight rates of approximation of mixed Nash equilibria by entropy regularization in continuous games UAI 2026 Tight Robustness Certification Through the Convex Hull of ℓ₀ Attacks AAAI 2026 Tight Sample Complexity Bounds for Entropic Best Policy Identification COLT 2026 Tight Sample Complexity of Transformers COLT 2026 TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability AAAI 2026 Time2Agri: Temporal Pretext Tasks for Agricultural Monitoring AAAI 2026 Time-aware Motion Planning in Dynamic Environments with Conformal Prediction L4DC 2026 TimeBill: Time-Budgeted Inference for Large Language Models AAAI 2026 TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting AAAI 2026 Time-Frequency Augmented Multi-level Contrastive Clustering for Time Series AAAI 2026 Time-Frequency Token Advantage Clipping for Training Efficient Large Reasoning Model AAAI 2026 TimeMachine-bench: A Benchmark for Evaluating Model Capabilities in Repository-Level Migration Tasks EACL 2026 TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding AAAI 2026 Time-Series Anomaly Detection with Graph-Based Self-Supervised Learning and Foundation Models: Towards Real-World Applications AAAI 2026 Time Series Class-Incremental Learning via Confidence-guided Mask Distillation and Prototype-guided Contrastive Learning AAAI 2026 Time Series Forecasting via Direct Per-Step Probability Distribution Modeling AAAI 2026