large language models

Guiding large language models to predict edit sequences for molecular synthesizability optimization

Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformation

The emergence of Large Language Models (LLMs) presents a dual challenge in the fight against disinformation. These powerful tools, capable of generating human-like text at scale, can be weaponised to produce sophisticated disinformation, yet they also hold promise for enhancing mitigation strategies. This paper investi...

A Statistical Perspective on Transformers for Small Longitudinal Cohort Data

ABSTRACT Modeling of longitudinal cohort data typically involves complex temporal dependencies between multiple variables. There, the transformer architecture, which has been highly successful in language and vision applications, allows us to account for the fact that the most recently observed time points in an indivi...

TRIAGE: Trustworthy Retrieval-based Interpretability with Abstention for Grounded Explanations in Clinical Decision Support System

TRIAGE: Trustworthy Retrieval-based Interpretability with Abstention for Grounded Explanations in Clinical Decision Support System The ability to provide explanations for Artificial Intelligence systems is increasingly important in healthcare, where predictive models support high‑stakes decisions but are often difficul...

"Is This Really a Human Peer Supporter?": Misalignments Between Peer Supporters and Experts in LLM-Supported Interactions

Mental health is a growing global concern, prompting interest in AI-driven solutions to expand access to psychosocial support. Peer support , grounded in lived experience, offers a valuable complement to professional care. However, variability in training, effectiveness, and definitions raises concerns about quality, c...

Case-knowledge-guided construction-phase safety appraisal report generation for hydraulic and hydropower projects using large language models

ScourFusion: A trustworthy large language model-augmented framework for automated extreme-aimed scour depth prediction under heterogeneous information

Validation of a Frozen LLM-Based Screening Instrument for Clinical Guideline Literature Screening

This preprint examines whether a fixed large language model configuration could safely support title-and-abstract screening in a planned evidence-synthesis workstream on clinical-guideline recommendations. The evaluation used a 1,048-record stratified calibration frame enriched for relevant records, rather than a repre...

rimi. — Open Convention for Conversational Reliability of LLMs

An open, collaborative and testable convention that sets what a large language model does when it would otherwise guess, smooth over or invent: ambiguous answers, conflicting sources, missing data, and resource use. Conformance levels A, AA, AAA with a separate frugality indicator S1, S2, S3.

VisKnacks: Agentic ParaView Visualization on HPC

Artificial intelligence can assist in prototyping scientific visualizations. To assist visualization experts, we introduce VisKnacks, an autonomous ParaView visualization agent enabled by large language models (LLMs). VisKnacks integrates multi-agent orchestration, retrieval-augmented generation, and containerized rend...

Appendix to the article: "An Industrial Evaluation of DeepQuali: Assessing User Story Quality with Large Language Models"

Appendix to the article: “An Industrial Evaluation of DeepQuali: Assessing User Story Quality with Large Language Models”

LLM-CodeSmell-Detection-AppInventor

This repository contains the implementation, datasets, prompts, and experimental results used in the study on code smell detection in MIT App Inventor applications using local Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).