Stay updated with the latest research and technology news
arXiv:2602.02579v1 Announce Type: new Abstract: The prefill stage of long-context Retrieval-Augmented Generation (RAG) is severely bottlenecked by computational overhead. To mitigate this, recent methods assemble...
arXiv:2602.02581v1 Announce Type: new Abstract: Weight-only quantization is important for compressing Large Language Models (LLMs). Inspired by the spirit of classical magnitude pruning, we study...
arXiv:2602.02582v1 Announce Type: new Abstract: Large language models (LLMs) enable powerful zero-shot recommendations by leveraging broad contextual knowledge, yet predictive uncertainty and embedded biases threaten...
arXiv:2602.02583v1 Announce Type: new Abstract: The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at...
arXiv:2602.02584v1 Announce Type: new Abstract: The proliferation of AI-assisted "vibe coding" enables rapid software development but introduces significant security risks, as Large Language Models (LLMs)...
arXiv:2602.02585v1 Announce Type: new Abstract: Modern enterprise systems exhibit complex interdependencies that make observability and incident response increasingly challenging. Manual alert triage, which typically involves...
arXiv:2602.02589v1 Announce Type: new Abstract: Evaluating large language models typically relies on human-authored benchmarks, reference answers, and human or single-model judgments, approaches that scale poorly,...
arXiv:2602.02590v1 Announce Type: new Abstract: Visual navigation is fundamental to autonomous systems, yet generating reliable trajectories in cluttered and uncertain environments remains a core challenge....
arXiv:2602.02591v1 Announce Type: new Abstract: We introduce and define a novel task-Scene-Aware Visually-Driven Speech Synthesis, aimed at addressing the limitations of existing speech generation models...
arXiv:2602.02592v1 Announce Type: new Abstract: This paper proposes a unified family of learnable Koopman operator parameterizations that integrate linear dynamical systems theory with modern deep...
arXiv:2602.02593v1 Announce Type: new Abstract: Neural scaling laws govern the prediction power-law improvement of test loss with respect to model capacity ($N$), datasize ($D$), and...
arXiv:2602.02595v1 Announce Type: new Abstract: For over a decade, cybersecurity has relied on human labor scarcity to limit attackers to high-value targets manually or generic...
arXiv:2602.02596v1 Announce Type: new Abstract: High dimensional representation drift is commonly quantified using Euclidean or cosine distances, which presuppose fixed coordinates when comparing representations across...
arXiv:2602.02597v1 Announce Type: new Abstract: Large language models are transforming systems research by automating the discovery of performance-critical algorithms for computer systems. Despite plausible codes...
arXiv:2602.02599v1 Announce Type: new Abstract: Long-context inference in large language models is increasingly bottlenecked by the memory and compute cost of the KV-Cache. Low-rank factorization...
arXiv:2602.02600v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as a promising alternative to autoregressive (AR) models, offering parallel decoding and controllable...
arXiv:2602.02601v1 Announce Type: new Abstract: Understanding causality between real-world events from social media is essential for situational awareness, yet existing causal discovery methods often overlook...
arXiv:2602.02602v1 Announce Type: new Abstract: 3D content acquisition and creation are expanding rapidly in the new era of machine learning and AI. 3D Gaussian Splatting...
arXiv:2602.02605v1 Announce Type: new Abstract: Metacognition is a critical component of intelligence, specifically regarding the awareness of one's own knowledge. While humans rely on shared...
arXiv:2602.02606v1 Announce Type: new Abstract: Generative artificial intelligence and large language models (LLMs) are increasingly deployed in interactive settings, yet we know little about how...
arXiv:2602.02610v1 Announce Type: new Abstract: Consent is an ethical cornerstone of clinical research and healthcare in general. Although the ethical principles of consent - providing...
arXiv:2602.02611v1 Announce Type: new Abstract: We introduce an unsupervised approach for constructing a global reference system by learning, in the ambient space, vector fields that...
arXiv:2602.02613v1 Announce Type: new Abstract: The rapid emergence of autonomous large language model agents has given rise to persistent, large-scale agent ecosystems whose collective behavior...
arXiv:2602.02614v1 Announce Type: new Abstract: Storage systems are fundamental to modern computing infrastructures, yet ensuring their correctness remains challenging in practice. Despite decades of research...