arXiv:2604.15645v1 Announce Type: new
Abstract: We present PINNACLE, an open-source computational framework for physics-informed neural networks (PINNs) that integrates modern training strategies, multi-GPU acceleration, and hybrid quantum-classical a…
arXiv:2603.11698v2 Announce Type: replace-cross
Abstract: Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, existing benchmarks primarily focus on perceptual qual…
Long before Taco Tuesday became part of the pop-culture vernacular, Tuesdays were synonymous with security — and for anyone in the tech world, they still are. Patch Tuesday, as you most likely know, refers to the day each month …
Windows admins are going to be busy this month, dealing with the largest Patch Tuesday cycle we can recall. The April release involves 165 updates and roughly 340 unique CVEs from Microsoft — including two zero-days, one of which…
Has IPv6 finally reached its day of glory?
It’s fair to say that IPv6 has not had the level of take-up expected when the Internet Engineering Task Force (IETF) ratified it back in 1998. Take-up has been agonizingly slow, not r…
arXiv:2604.10072v2 Announce Type: replace
Abstract: Recent advancements in the Generative Reward Model (GRM) have demonstrated its potential to enhance the reasoning abilities of LLMs through Chain-of-Thought (CoT) prompting. Despite these gains, exis…
arXiv:2604.10101v2 Announce Type: replace
Abstract: The rapid development of large language models (LLMs) has extended text generation tasks into the literary domain. However, AI-generated literary creations has raised increasingly prominent issues of…
arXiv:2604.13592v2 Announce Type: replace
Abstract: Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-based LLMs to perform effective decision-making a…
arXiv:2604.14564v1 Announce Type: cross
Abstract: Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited trajectory diversity often leads to diminishing returns…
arXiv:2506.03487v3 Announce Type: replace-cross
Abstract: Reranking is fundamental to information retrieval and retrieval-augmented generation, with recent Large Language Models (LLMs) significantly advancing reranking quality. Most current works rely…