Machine Learning

Improving Large Language Model Safety with Contrastive Representation Learning EMNLP 2025 Improving Large Vision and Language Models by Learning from a Panel of Peers ICCV 2025 Improving LLM Reasoning through Interpretable Role-Playing Steering EMNLP 2025 Improving LLM Safety Alignment with Dual-Objective Optimization ICML 2025 Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens ICML 2025 Improving LLM Video Understanding with 16 Frames Per Second ICML 2025 Improving Long-Text Alignment for Text-to-Image Diffusion Models ICLR 2025 Improving Low-Resource Morphological Inflection via Self-Supervised Objectives ACL 2025 Improving Low-Resource Sequence Labeling with Knowledge Fusion and Contextual Label Explanations EMNLP 2025 Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback ACL 2025 Improving MLLM’s Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency ACL 2025 Improving Model Evaluation using SMART Filtering of Benchmark Datasets NAACL 2025 Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels AAAI 2025 Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques ICML 2025 Improving Multilingual Sign Language Translation with Automatically Clustered Language Family Information COLING 2025 Improving Multimodal Learning via Imbalanced Learning ICCV 2025 Improving Multimodal Social Media Popularity Prediction via Selective Retrieval Knowledge Augmentation AAAI 2025 Improving Named Entity Recognition for Low-Resource Languages Using Large Language Models: A Ukrainian Case Study ACL 2025 Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis AAAI 2025 Improving Neural Network Accuracy by Concurrently Training with a Twin Network ICLR 2025 Improving Neural Optimal Transport via Displacement Interpolation ICLR 2025 Improving Neutral Point-of-View Generation with Data- and Parameter-Efficient RL EMNLP 2025 Improving N-Glycosylation and Biopharmaceutical Production Predictions Using AutoML-Built Residual Hybrid Models AISTATS 2025 Improving NMT Models by Retrofitting Quality Estimators into Trainable Energy Loss COLING 2025 Improving Noise Efficiency in Privacy-preserving Dataset Distillation ICCV 2025