large language models

Computational materials agents: from task demonstrations to executable scientific workflows

This review examines how current systems translate materials questions into computational tasks, identifies the settings in which reliability and recovery have been demonstrated, and explains why runnable calculations should be distinguished from scientifically justified conclusions.

Evaluating the feasibility, effectiveness, and acceptability of AI-chatbot support in an online intervention for female sexual dysfunction

Distressing low sexual desire is the most prevalent sexual dysfunction among women. One treatment option is eSense, an effective digital tool delivering mindfulness-based therapy (MBT). It integrates human “navigators” to support users and, though they improve eSense adherence, may be costly during scale-up. Large lang...

PegasusAI: Next-Generation AI-Driven Scientific Workflow Management

Pegasus AI is developing an AI-driven scientific workflow management system that combines machine learning, large language models, online monitoring, and human guidance to support the workflow lifecycle. It helps scientists create workflows, predict resource requirements, monitor execution, diagnose failures, and adapt...

Data and code for "Humans and large language models rely on distinct strategies for adaptive decision-making under uncertainty"

human vs LLM in adaptive decision making, including four reinforcement learning tasks(one-armed, two-armed bandit tasks, reversal learning task and two-step task)

ARES: Securing Agents for Computer Use Through Endpoint Resource Mediation and Behavioral Guardrails

Large language model (LLM)-based agents are evolving into agents for computer use (ACUs) that read files, invoke applications, communicate over networks, and operate graphical interfaces, moving the effective security boundary from model inputs and outputs to autonomous actions that alter endpoint state. Conventional i...

Hallucinations in Structured Extraction: A Case Study on Prompt-Based Semantic Role Labeling

This paper studies hallucinations in structured extraction using prompt-based Semantic Role Labeling (SRL) as a controlled case study. We implement a DSPy-based pipeline in which each prediction includes a generated rationale and a citation to a governing rule, allowing extraction errors to be aggregated by attributed...

Forecasting the FIFA World Cup 2026 with Large Language Models: A Benchmark of Reasoning, Web-Augmented, Agentic, and Open-Weight AI Systems

It is suggested that reasoning alone is not sufficient for tournament forecasting when the task depends on current squads, recent performance, injuries, rankings, and evolving football context, and this study provides a reproducible evaluation framework for large language model-based sports forecasting.

Hybrid Architecture of Intelligent Systems with a Deterministic Core: from Concept to Prototype

The rapid development of large language models and autonomous intelligent agents has significantly expanded the capabilities of natural language processing and decision support. However, practical implementation reveals fundamental limitations, particularly in tasks requiring computational robustness, reproducibility o...

Large language models for population-level public health communication: an evidence map of deployment, reach and policy gaps

Preprint version 6 (posted 4 September 2026). This version supersedes versions 1–5 and should be used in preference to them. Versions 1–5 were posted on 6 April, 3 June and 4 June 2026. What changed, and why. Version 6 reports a corrected re-analysis carried out after peer review. An audit of the data-charting pipeline...

Consumer Wearable Devices for Population-Level Infectious Disease Surveillance: A Scoping Review

Preprint, version 2. This manuscript has not been peer reviewed. It is under consideration at a peer-reviewed journal. This version supersedes version 1 (10.5281/zenodo.19411761, April 2026), which should no longer be cited for any numerical result. The review was rebuilt rather than amended, and the two versions do no...

BigMixSolDB: Extraction of a solubility database in solvent mixtures with an uncertainty-quantified large language model-based pipeline

Supplementary material for the publication "BigMixSolDB: Extraction of a solubility database in solvent mixtures with an uncertainty-quantified large language model-based pipeline". This Zenodo record contains the data and supporting materials for BigMixSolDB, a workflow for extracting experimental solubility data from...

ProGRank: Probe-Gradient Reranking to Defend Dense-Retriever RAG from Corpus Poisoning