Quality follows upgrading
Academic
arXiv:2603.11067v1 Announce Type: new Abstract: Large language models (LLMs) achieve remarkable performance, yet further gains often require costly training. This has motivated growing interest in …
arXiv:2603.11455v1 Announce Type: new Abstract: This study examines users' behavioural intention to use OpenClaw through the Cognition--Affect--Conation (CAC) framework. The research investigates how cognitive perceptions …
arXiv:2603.11281v1 Announce Type: new Abstract: Medical question-answering benchmarks predominantly evaluate single-turn exchanges, failing to capture the iterative, clarification-seeking nature of real patient consultations. We introduce …
arXiv:2603.11798v1 Announce Type: new Abstract: Multi-document Multi-entity Question Answering inherently demands models to track implicit logic between multiple entities across scattered documents. However, existing Large …
arXiv:2603.11818v1 Announce Type: new Abstract: The unrestrained proliferation of cells that are malignant in nature is cancer. In recent times, medical professionals are constantly acquiring …
arXiv:2603.11781v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly tackle complex reasoning, yet their interaction patterns remain limited to voting, unstructured debate, or pipeline orchestration. …
arXiv:2603.11409v1 Announce Type: new Abstract: Existing voice AI assistants treat every detected pause as an invitation to speak. This works in dyadic dialogue, but in …
arXiv:2603.11864v1 Announce Type: new Abstract: As AI agents are increasingly used in high-stakes domains like healthcare and law enforcement, aligning their behaviour with social, legal, …
arXiv:2603.11767v1 Announce Type: new Abstract: This paper presents an in-depth analysis of Wikidata qualifiers, focusing on their semantics and actual usage, with the aim of …
arXiv:2603.11394v1 Announce Type: new Abstract: Patients and clinicians are increasingly using chatbots powered by large language models (LLMs) for healthcare inquiries. While state-of-the-art LLMs exhibit …
arXiv:2603.11709v1 Announce Type: new Abstract: While scaling laws for Large Language Models (LLMs) have been extensively studied along dimensions of model parameters, training data, and …
arXiv:2603.11245v1 Announce Type: new Abstract: As NLP evaluation shifts from static benchmarks to multi-turn interactive settings, LLM-based simulators have become widely used as user proxies, …