arXiv:2604.21724v2 Announce Type: replace
Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and rapid memory growth. We attribute these limita…
arXiv:2509.20979v2 Announce Type: replace
Abstract: In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as \textsc{LRU} can perform far worse than the offline optimum. Existing learning-based caching syste…
arXiv:2601.23022v3 Announce Type: replace
Abstract: Aspect-Based Sentiment Analysis (ABSA) focuses on extracting sentiment at a fine-grained aspect level and has been widely applied across real-world domains. However, existing ABSA research relies on …
arXiv:2604.22192v1 Announce Type: new
Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are fundamentally constrained by data-centric limitatio…
arXiv:2510.12328v5 Announce Type: replace
Abstract: Accurate rainfall forecasting, particularly for extreme events, remains a significant challenge in climatology and the Earth system. This paper presents novel physics-informed Graph Neural Networks (…
arXiv:2604.22348v1 Announce Type: new
Abstract: Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising approach for leveraging large-scale unlabeled healthca…
arXiv:2604.22240v1 Announce Type: new
Abstract: Generative world models increasingly rely on 4D occupancy for realistic autonomous driving simulation. However, existing generation frameworks depend on rigid geometric conditions (e.g., explicit traject…
arXiv:2504.06148v3 Announce Type: replace
Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existing static image-text benchmarks are insufficient fo…
arXiv:2602.21750v2 Announce Type: replace
Abstract: Protein language models (PLMs) have become widely adopted as general-purpose models, demonstrating strong performance in protein engineering and de novo design. Like large language models (LLMs), the…
Meta is continuing its compute grab as the agentic AI race accelerates to a sprint.
Today, the company announced a partnership with Amazon Web Services (AWS) that will bring “tens of millions” of AWS Graviton5 cores (one chip …