For An Exciting Tomorrow
arXiv:2506.13119v1 Announce Type: cross Abstract: Identifying causative genes from patient phenotypes remains a significant challenge in precision medicine, with important…
arXiv:2506.10669v2 Announce Type: replace-cross Abstract: Background and Objective: Prototype-based methods improve interpretability by learning fine-grained part-prototypes; however, their visualization in…
arXiv:2506.11526v1 Announce Type: cross Abstract: For autonomous vehicles, safe navigation in complex environments depends on handling a broad range of…
arXiv:2506.11543v1 Announce Type: cross Abstract: Post-training quantization (PTQ) has stood out as a cost-effective and promising model compression paradigm in…
arXiv:2506.10848v2 Announce Type: replace-cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to traditional autoregressive LLMs by…
arXiv:2506.11012v1 Announce Type: new Abstract: Knowledge graphs (KGs) have emerged as a powerful paradigm for structuring and leveraging diverse real-world…
arXiv:2506.10821v1 Announce Type: cross Abstract: Long video understanding (LVU) presents a significant challenge for current multi-modal large language models (MLLMs)…
arXiv:2506.09820v2 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) like o1 and DeepSeek-R1 have shown remarkable progress in natural language…