Mass religious gatherings such as the Kumbh Mela concentrate tens of millions of people into a single region over a few weeks, producing intense, repetitive, multilingual, and safety-critical demand for information. The default response, a conversational assistant that routes every query to a large language model (LLM)...
Context: Generative AI (GenAI) and Large Language Models (LLMs) are increasingly used for academic tasks in software engineering and beyond, including systematic literature reviews (SLRs). However, whilst their capabilities are rapidly developing, there is no guarantee they can meet the rigour, reliability, and transpa...
Barbara Kitchenham, Sebasti\'an Pizard, Lech Madeyski et al.· 0 citations
A human-in-the-loop AI agent that assembles a dossier of sourced evidence for each scholar and drafts one-sentence Translational Science Benefits Model (TSBM) impact summaries for staff review and found the agent's recall close to human search.
Mohammad Arvan, Amber E. Osterholt, Baile Rue et al.· arXiv.org· 0 citations
Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabilities, uncertainty estimation, and selective referral, particularly under dataset shift.
Methods: We developed a calibrated deterministic five-member deep ensemble for R...
Md. Sadibul Hasan Sadib, Md. Mohayminul Mukit, Rahmatul Kabir Rasel Sarker et al.· 0 citations
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The findings show that training-free reference-based attribution should be understood as the interaction between where images are compared, how the reference set is constructed, and how many references are available, and that attribution accuracy generally peaks at intermediate representation levels.
Meiling Li, Pietro Bongini, Benedetta Tondi et al.· arXiv.org· 0 citations
Most instruments for measuring political positions, such as manifesto coding, expert surveys and text-scaling models, were built and validated on Western party systems, and they break down worst where many consequential actors never publish a manifesto, never contest a competitive election, or commit one position to a...
Large language model (LLM)-based approaches for automated code compliance (ACC) of building regulations are prone to generating incorrect and hallucinated computer-processable rules. This paper introduces P4IR, a two-stage framework that uses supervised fine-tuning (SFT) to instill domain knowledge in an LLM, followed...
Jack Wei Lun Shi, Minghao Dang, Wawan Solihin et al.· 0 citations
The results demonstrate that TransitNet provides an accurate, scalable, and computationally efficient framework for low-SNR transit blind searches in the tested regime and motivate its extension to longer-period Earth-size planet searches.
Xing-Chen Yan, Jian Ge, Qing-Tian Liu et al.· arXiv.org· 0 citations
Effective human-robot teamwork requires robots to adapt to partners, situations, and task dynamics from the start of an interaction. In the MATRX Urban Search and Rescue (USAR) environment, people can externalize collaboration patterns (CPs) they discover during teamwork through a chat and reflection interface. We stud...
Taewoon Kim, Emma van Zoelen, Mark Neerincx· 0 citations
Discharge summaries are crucial clinical documents containing the context of a patient's overall hospital stay, and are routinely reviewed by medical experts for patient readmission, ongoing care, and diagnostic decision-making. When reviewing them, medical experts often must iteratively synthesize information across m...
Jiyoun Kim, Muhan Yeo, Eunhye Jang et al.· 0 citations
It is argued that a robust proof autoformalizer must remain faithful even for informal proofs that diverge from these idealized ones, and the first study on the robustness of proof autoformalization models is presented.
Adapting Large Language Models (LLMs) to specific tasks usually involves fine-tuning: Low-Rank Adaptation (LoRA) edits the weights, while soft prompting prepends trainable virtual tokens. Both change how an already-optimized model is served, so serving many task-specific adapters at high throughput requires adapter-awa...
Michal Chudoba, Sergey Alyaev, Petra Galuscakova et al.· 0 citations
