Deep Learning

What Matters in Learning from Large-Scale Datasets for Robot Manipulation ICLR 2025 What Matters When Repurposing Diffusion Models for General Dense Perception Tasks? ICLR 2025 What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs ACL 2025 What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models ICLR 2025 What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization ICCV 2025 What’s in a prompt? Language models encode literary style in prompt embeddings EMNLP 2025 What's in the Image? A Deep-Dive into the Vision of Vision Language Models CVPR 2025 What's Making That Sound Right Now? Video-centric Audio-Visual Localization ICCV 2025 What to Distill? Fast Knowledge Distillation with Adaptive Sampling ICCV 2025 What to Predict? Exploring How Sentence Structure Influences Contrast Predictions in Humans and Large Language Models NAACL 2025 What to Preserve and What to Transfer: Faithful, Identity-Preserving Diffusion-based Hairstyle Transfer AAAI 2025 When2Call: When (not) to Call Tools NAACL 2025 When Anchors Meet Cold Diffusion: A Multi-Stage Approach to Lane Detection ICCV 2025 When and How Does CLIP Enable Domain and Compositional Generalization? ICML 2025 When and How to Augment Your Input: Question Routing Helps Balance the Accuracy and Efficiency of Large Language Models NAACL 2025 When and Where do Data Poisons Attack Textual Inversion? ICCV 2025 When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMs EMNLP 2025 When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? AAAI 2025 When Cars Meet Drones: Hyperbolic Federated Learning for Source-Free Domain Adaptation in Adverse Weather WACV 2025 When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need ICML 2025 When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets ICML 2025 When do GFlowNets learn the right distribution? ICLR 2025 When do neural networks learn world models? ICML 2025 When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration ICML 2025 When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network ICML 2025