arXiv:2508.10528v1 Announce Type: cross Abstract: Medical image grounding aims to align natural language phrases with specific regions in medical images, […]
arXiv:2508.09383v1 Announce Type: cross Abstract: We present X-UniMotion, a unified and expressive implicit latent representation for whole-body human motion, encompassing
arXiv:2508.09458v1 Announce Type: cross Abstract: Knowledge syntheses (literature reviews) are essential to health professions education (HPE), consolidating findings to advance
arXiv:2508.09497v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems are often bottlenecked by their reranking modules, which typically score passages
arXiv:2508.09330v1 Announce Type: cross Abstract: Synaptic pruning in biological brains removes weak connections to improve efficiency. In contrast, dropout regularization
Synaptic Pruning: A Biological Inspiration for Deep Learning Regularization Lire l’article »
arXiv:2508.09537v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for function completion in repository-scale codebases. Prior studies
arXiv:2504.00043v2 Announce Type: replace-cross Abstract: Existing reasoning evaluation frameworks for Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) predominantly
arXiv:2410.23279v4 Announce Type: replace-cross Abstract: The marmoset, a highly vocal primate, is a key model for studying social-communicative behavior. Unlike
arXiv:2508.06671v2 Announce Type: replace-cross Abstract: The impressive performance of language models is undeniable. However, the presence of biases based on
Do Biased Models Have Biased Thoughts? Lire l’article »
arXiv:2506.14412v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enriches Large Language Models (LLMs) by combining their internal, parametric knowledge with