Abstract We explore how large language models (LLMs) can enhance the proposal selection process at large user facilities, offering a scalable, consistent, and cost-effective alternative to traditional human review. Proposal selection depends on assessing the relative strength among submitted proposals; however, traditi...
Lijie Ding, Janell Thomson, Jon Taylor et al.· Scientific Reports· 0 citations
The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinical decision-making. However, few have been tailored for ophthalmology, and most evaluations focus mainly on knowledge-based QA without clinic...
Hyunjae Kim, X. C. Ai, Sahana Srinivasan et al.· npj Digital Medicine· 1 citation
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Malva Malva is an artifact for studying tool-mediated interaction failures in agentic GUI software. It contains a defect library built from 40 open-source applications, a task suite for reproducing representative failures, and MalvaGuard, a static checker that detects missing tool-interaction guards before agent execut...
Abstract Large Language Models (LLMs) have shown high capabilities in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. However, training these models requires massive amount of data and significant computational resources. Adapters are specializ...
Meghdad Dehghan, Jie JW Wu, Fatemeh H. Fard et al.· Empirical Software Engineeri...· 1 citation
Objective This study experimentally tested whether language and cultural prompts would influence large language models' (LLMs) assessments and recommendations when presented with the same mental health description. Methods We conducted two experiments employing a 2 (language prompting: Chinese vs. English) x 2 (cultura...
Abstract: Modern automated computing systems increasingly deploy Large Language Models (LLMs) to resolve runtime operational triage, incurring prohibitive latency (>100–500 ms), severe memory allocation (>4–8 GB VRAM), and high thermodynamic dissipation. Extending the foundational theory of Mandelbrot Fractal Neural Sy...
Early screening via colonoscopy is critical for colon cancer prevention, yet developing robust AI systems for this domain is hindered by the lack of densely annotated, long-sequence video datasets. Existing datasets predominantly focus on single-class polyp detection and lack the rich spatial, temporal, and linguistic...
Abdullah Hamdi, Changchun Yang, Xin Gao· Lecture notes in computer sc...· 0 citations
The ubiquity of Large Language Models (LLMs) is driving a paradigm shift where user convenience supersedes computational efficiency. This article defines the "Plausibility Trap": a phenomenon where individuals with access to Artificial Intelligence (AI) models deploy expensive probabilistic engines for simple determini...
Iván Carrera, Daniel Maldonado-Ruiz· Computer· 0 citations
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026