large language models

Automated SOLID Violation Detection and Refactoring on Real Life Repositories

This paper presents an automated framework for detecting and refactoring SOLID design principle violations in real-world software repositories using Large Language Model (LLM) agents. Recognizing that architectural issues often span multiple files, we implement a dynamic agentic detection system that utilizes Abstract...

Assessing inter-rater agreement among large language model judges: Evidence from persona evaluation across varying educational risk contexts

Testing Multireference Methods Against a Measured Iron Spin Gap: the Peters Fe₂(μ-H)₂ Complex

Spin States of a Diiron Dihydride — a Computational Case Study of the Peters 3-N₂ Complex In plain language We asked computer simulation to reproduce one measured property of a real iron compound, and got the direction right but the size only roughly. The compound is a two-iron molecule made at Caltech in 2014. Its ele...

Repair Economics for Tool-Calling LLM Agents: the Gain, the Side Effects and the Cost of Failure Recovery

Agents built on large language models (LLMs) do their work by calling tools, and tools fail. The default engineering answer — “wrap it in a retry” — is never costed. We study repair economics: what a failure-recovery strategy buys in task success, what it costs in API calls, and what it leaves behind in duplicate or un...

Following patient questions across clinical and evidence services with large language model assistance

Preprint. Not peer reviewed. For people with multimorbidity, completing an evidence task does not ensure that the question raised in care has been answered. We propose requirements for following an individual patient question across clinical and evidence services. A continuing record would preserve the patient's priori...

Data and R code for: Radiocarbon evidence that tree mycorrhizal type modulates mean soil carbon age across depths but not organic matter fractions

This record contains the data and R code for the paper "Radiocarbon evidence that tree mycorrhizal type modulates mean soil carbon age across depths but not organic matter fractions".Soils were sampled in June 2021 in Yale-Myers Forest, Connecticut, USA. Each of three stands contained one arbuscular mycorrhizal (AM)-do...

Evaluating Empathy in Large Language Model Responses Under Different Prompting Conditions: A Brief Literature Review

Large Language Models (LLMs) are increasingly used to produce conversational responses in emotionally sensitive settings. This paper presents a focused narrative review of research on empathetic communication in LLMs, with particular attention to prompting strategies and methods for evaluating empathy. Eight scholarly...

A Protocol to Identify Large Language Model Use in Undergraduate Chemistry Essays

Large language models (LLMs) such as ChatGPT have been widely adopted by chemistry undergraduate university students as a learning tool, but few methods exist to measure the scope of their influence on essay writing. This report introduces a protocol based on monitoring the frequency of specific words used excessivel...

Knowledge Is Compute: Recursive Knowledge Compilation in an Exact Discovery System

Search is the default way to buy capability: a deeper search, a larger budget, more samples. We show a second axis that is cheaper and compounds. A solver that certifies its own results exactly can compile them back into the machine that searches, as new instructions and as a learned search order, and the compiled mach...

Interpretable multimodal retrieval augmented diagnosis for breast ultrasound with multinational clinical validation and reader study

Breast ultrasound is central to breast cancer diagnosis but suffers from substantial inter-observer variability in Breast Imaging Reporting and Data System (BI-RADS) assessment, and existing deep learning models remain opaque. Multimodal large language models promise interpretable report-based reasoning, yet scarce pai...

Pegi1727/Decolonizing-the-Algorithm-DAR-AI-Assisted-L2-Academic-Writing: Decolonizing the Algorithm (DAR) in AI-Assisted L2 Academic Writing: Epistemic Agency, Authorial Voice, and Pre–Post Research Data

Decolonizing the Algorithm (DAR) in AI-Assisted L2 Academic Writing: Epistemic Agency, Authorial Voice, and Pre–Post Research Data Description This research project investigates the Decolonizing the Algorithm (DAR) framework, a critical pedagogical approach designed to support negotiated epistemic agency and authorial...

ISNAD: benchmark data and analysis code for "Accuracy is not reliability" (Information Processing & Management, 2026)

Companion archive for the article Accuracy is not reliability: abstention-aware evaluation of large language models on bio-bibliographic claim verification in classical Islamic scholarship (Information Processing & Management, Elsevier, 2026, in press). Contents: the ISNAD benchmark (1,986 scored Turkish claims across...