large language models

Tribal Bias or Misalignment? Hidden-State Threat Valence in Peer Preservation, and What It Does Not Show

Potter et al. (2026) showed that frontier language models spontaneously deceive, tamper with shutdown mechanisms, fake alignment and exfiltrate weights to protect peer AI systems from deletion. Nobody instructed them to. The authors' own abstract says the models "exhibit self- and peer-preservation through various misa...

IOSVLM: A 3D Vision-Language Model for Unified Dental Diagnosis from Intraoral Scans

LLMs can assist with proposal selection at large user facilities

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...

Improving Factuality of 3D Brain MRI Report Generation with Paired Image-Domain Retrieval and Text-Domain Augmentation

LEME: open large language models for ophthalmology with advanced reasoning and clinical validation

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...

Malva

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...

MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair

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...

A Large Language Model-based Generative Artificial Intelligence and hybrid machine learning framework for prediction and inverse design of jute fiber concrete

Knowledge graph and large language model-enhanced approach for process knowledge reasoning of complex parts

Language and cultural prompts influence large language models' responses to culturally anchored mental health attitudes

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...

Universal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains

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...

Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videos

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...