Artificial Intelligence

Mitigating Subgroup Disparities in Multi-Label Speech Emotion Recognition: A Pseudo-Labeling and Unsupervised Learning Approach Interspeech 2025 Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace ICLR 2025 Mitigating the Discrepancy Between Video and Text Temporal Sequences: A Time-Perception Enhanced Video Grounding method for LLM COLING 2025 Mitigating the Human-Robot Domain Discrepancy in Visual Pre-training for Robotic Manipulation CVPR 2025 Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data EMNLP 2025 Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning ACL 2025 Mitigating Visual Knowledge Forgetting in MLLM Instruction-tuning via Modality-decoupled Gradient Descent EMNLP 2025 MixANT: Observation-dependent Memory Propagation for Stochastic Dense Action Anticipation ICCV 2025 Mixed-Curvature Multi-Modal Knowledge Graph Completion AAAI 2025 Mixed Patch Visible-Infrared Modality Agnostic Object Detection WACV 2025 Mixed Signals: Decoding VLMs’ Reasoning and Underlying Bias in Vision-Language Conflict EMNLP 2025 Mixed Signals: Understanding Model Disagreement in Multimodal Empathy Detection IJCNLP 2025 MixEval-X: Any-to-any Evaluations from Real-world Data Mixture ICLR 2025 Mixing Inference-time Experts for Enhancing LLM Reasoning EMNLP 2025 Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN ICLR 2025 MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora EMNLP 2025 MixMin: Finding Data Mixtures via Convex Minimization ICML 2025 MixRI: Mixing Features of Reference Images for Novel Object Pose Estimation ICCV 2025 Mixture Compressor for Mixture-of-Experts LLMs Gains More ICLR 2025 Mixture-of-Agents Enhances Large Language Model Capabilities ICLR 2025 Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models ACL 2025 Mixture of Experts Made Intrinsically Interpretable ICML 2025 Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models ICLR 2025 Mixture of insighTful Experts (MoTE): The Synergy of Reasoning Chains and Expert Mixtures in Self-Alignment ACL 2025 Mixture of Knowledge Minigraph Agents for Literature Review Generation AAAI 2025