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large language models

2,378 papers

#large language models Open access Oct 2026

eData: A tool and format for rapid extraction of exposure data from scientific articles

Abstract Extracting and formatting data is among the most tedious elements of assessing environmental chemical occurrence and exposure. We present a toolkit (eData) to streamline this process, generate FAIR data, and maximise traceability and transparency: a FAIR Data Reporting Format (DRF) that provides data structure...

Samuel A. Welch, Knut Erik Tollefsen · 0 citations
#large language models Open access Oct 2026

Ensemble Voting of Large Language Models for Multiple-Choice Answer Prediction

Machine Reading Comprehension (MRC) has become a key benchmark for evaluating natural language processing systems, and multiple-choice question answering is widely adopted for assessing reasoning, comprehension, and commonsense inference capabilities. However, traditional embedding-based approaches often struggle with...

Wen‐Hao Lee, Ray-I Chang, Show-Jane Yen et al. · 0 citations
#large language models Open access Oct 2026

Deterministic Promotion of Findings in Agentic Offensive Security: Verifier Oracles over LLM-as-Judge

This research presents RootViel, an agentic offensive-security platform built on the MINERVA engine, introducing a deterministic approach to verifying security findings generated by autonomous AI agents. The work addresses a fundamental limitation of contemporary multi-agent security systems: the reliance on Large Lang...

Alejandro Jaime · 0 citations
#large language models Review Open access Oct 2026

AI-Driven Feedback on Bitewing Radiographic Technique: A Comparative Study of Large Language Models.

INTRODUCTION Large language models (LLMs) can enhance learning engagement and accessibility, though their performance in dentistry is inconsistent. Bitewing radiographs are critical for caries detection but prone to diagnostic errors from operator positioning. This study compared the performance of four LLMs with reaso...

K. Rabelo, Laura Swinckles, Eduardo Delamare et al. · 0 citations
#large language models Open access Oct 2026

Symmetry-Transport Hypernetworks: Efficient On-Demand Weights by Separating Task Geometry from Conditional Parameter Generation

A hypernetwork can generate task-specific model weights from a compact representation of the task, rather than learning a separate set of weights for every transformed version. In this work, invariant task coordinates are used to generate canonical weights, which are then transformed according to the known task symmetr...

Chanayut Theslongthong · 0 citations
#large language models Open access Oct 2026

DBCLS BioHackathon 2026 report: An interactive, harmonised BioSample metadata resource for biological sample discovery

The BioSample database contains tens of millions of records describing biological samples, but their metadata are submitted largely as key--value pairs with inconsistent field names, terminology and free-text descriptions, limiting search and reuse. Before the DBCLS BioHackathon 2026, we used a pipeline based on locall...

Shuya Ikeda, Núria Fabrega, Hirotaka Suetake et al. · 0 citations
#large language models Open access Oct 2026

Performance Limitations of Large Language Models in Processing Low-Resource Regional Languages: Empirical Evidence and Pre-Training Optimization Strategies

While Large Language Models (LLMs) such as ChatGPT and Gemini have transformed information processing in resource-rich languages, their effectiveness significantly diminishes when applied to low-resource regional languages (e.g., Sundanese and Javanese). This paper investigates the performance bottlenecks experienced b...

Zivanna Rengganis Suparman · 0 citations
#large language models Review Open access Oct 2026

AI chatbot-associated psychiatric symptoms: a narrative review of publicly available reports and media accounts

Abstract Background There are a growing number of cases where direct use of AI has been associated with either new or worsening psychiatric symptoms (colloquially labelled AI psychosis). Due to the novelty of the phenomenon, current literature is limited on the impacts of sustained, emotionally charged interactions wit...

Ankith Arun, Christina Trinh, Waguih William IsHak · 0 citations
#large language models Open access Oct 2026

Gene-level evolutionary conservation and human constraint decline at comparable rates across the age of onset of Mendelian disease

Background Gene-level constraint and conservation scores are widely used to prioritise disease genes and to benchmark genomic language models. Purifying selection acts weakly on phenotypes manifesting after reproduction, so these scores are expected to carry less information about late-onset disease. An onset-dependent...

Anees Ahmed Mahaboob Ali, Everette Jacob Remington Nelson · 0 citations
#large language models Open access Oct 2026

x3d_mcp: A Model Context Protocol Server for AI-Assisted X3D Authoring

Large language models (LLMs) are increasingly capable of generating structured technical content, but producing valid Extensible 3D (X3D) scenes is brittle in practice: without grounding in the authoritative specification, LLMs hallucinate node names, misuse field types, and emit broken ROUTE connections that fail XSD...

Nikhil Narra, Rick Lentz, Don Brutzman et al. · 0 citations
#large language models Open access Oct 2026

“Oh No, the Robots Are Here”: AI identity labels, social uptake and sanctioning in mixed human–AI communities

Social media users can now encounter autonomous AI accounts that post, reply and vote alongside other users. In a longitudinal field experiment, we examined how labelling these accounts relates to whom people answer and how they evaluate AI contributions. YSocial is a Reddit-like hybrid platform for social media simula...

Sara Major, Aleksandar Tomašević, Ana Vranić et al. · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

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