Quality follows upgrading
All Articles
arXiv:2603.10002v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly tasked with producing and manipulating structured artifacts. We consider the task of end-to-end spreadsheet …
arXiv:2603.09995v1 Announce Type: cross Abstract: Behavioral interview evaluation using large language models presents unique challenges that require structured assessment, realistic interviewer behavior simulation, and pedagogical …
arXiv:2603.09983v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable scalable performance but face severe memory constraints on edge devices. Existing offloading strategies struggle with I/O …
arXiv:2603.09989v1 Announce Type: cross Abstract: We introduce the System Hallucination Scale (SHS), a lightweight and human-centered measurement instrument for assessing hallucination-related behavior in large language …
arXiv:2603.09999v1 Announce Type: cross Abstract: This paper presents the design and validation of a retrieval-based assistant that supports safety assessment, certification activities, and regulatory compliance …
arXiv:2603.09998v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) have exceptional performance in machine translation, only a limited systematic assessment of translation quality has …
arXiv:2603.10600v1 Announce Type: new Abstract: LLM-powered agents face a persistent challenge: learning from their execution experiences to improve future performance. While agents can successfully complete …
arXiv:2603.10005v1 Announce Type: cross Abstract: Many Automatic Speech Recognition (ASR) applications require streaming processing of the audio data. In streaming mode, ASR systems need to …
arXiv:2603.10359v1 Announce Type: new Abstract: Distilling reasoning capabilities from Large Reasoning Models (LRMs) into smaller models is typically constrained by the limitation of rejection sampling. …
arXiv:2603.09994v1 Announce Type: cross Abstract: Compositionality is considered central to language abilities. As performant language systems, how do large language models (LLMs) do on compositional …
arXiv:2603.09985v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse tasks, yet their ability to accurately assess their own confidence …
arXiv:2603.09996v1 Announce Type: cross Abstract: The integration of large language models (LLMs) into educational processes introduces significant constraints regarding data privacy and reliability, particularly in …