large language models

Mechanistic understanding and peptide ingredient screening for type III collagen via biological knowledge graph and molecular docking

Abstract Objective Type III collagen plays a key role in maintaining skin elasticity and dermal resilience, yet its decline is associated with visible signs of skin ageing. This study aimed to establish a data‐driven approach to identify cosmetic peptides with potential to enhance type III collagen through multi‐target...

Comparing Human‐Created and NotebookLM‐Generated Podcasts for EAP Instruction: Differences in Linguistic Complexity and the Role of Prompt Design

ABSTRACT Science popularization podcasts are valuable resources for EAP instruction because they make academic content more accessible to learners. However, producing high‐quality podcasts is time‐consuming and resource‐intensive, and existing resources may not always align with instructional goals or learners’ needs....

DEL-GPT: learning the language of DNA-encoded libraries to design focused screening collections

Focused DNA-encoded libraries (DELs) yield higher hit rates and cleaner selection data than billioncompound collections, and are affordable enough to build for a single target. Designing one means choosing a few hundred synthons from a much larger pool, and in the split-and-pool format that choice is collective and irr...

A review of bias detection and fairness auditing techniques in LLMs

A thorough literature review is provided to encapsulate prior research on bias identification and fairness auditing, categorizing the findings according to various stages of study and proposing a unified pipeline for dataset integration and a modular framework for bias auditing.

Adapting NDBIs for Autistic Children Who Use Echolalia: A Cascading Coaching Approach to Supporting Communication and Language Development

This pilot study examined a cascading coaching model to train graduate student clinicians and caregivers to use adapted Naturalistic Developmental Behavioral Intervention (NDBI) techniques with autistic preschoolers who use echolalia. Adaptations were designed to incorporate children’s echolalic speech within intervent...

SciRep: A Ranking-Aware Representation Model for Scientific Text

Results demonstrate that the proposed ranking-aware distillation mechanism significantly enhances scientific text representation quality while maintaining efficient inference, offering a more effective contrastive learning method for domain-specific retrieval tasks.

Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases

A cornea-specialized large language model enhanced with RAG improved diagnostic accuracy in complex corneal cases, particularly among clinicians with lower baseline performance.

Retrieval Augmented Generation for Relative Distance-based Spatial Reasoning

Large Language Models (LLMs) can be applied to various real-world tasks, many of which require spatial reasoning, like pattern-based spatial search, Point of Interest (POI) recommendation, and itinerary or travel planning. However, on their own LLMs have been shown to lack reliable spatial reasoning capabilities, espec...

Generative large language models in medicine: a scoping review of recent methodological advances

By tracing the evolutionary trajectories of these methodologies, this scoping review provides a mechanism-centered framework to inform responsible model development and deployment in medical settings, tailored to task complexity, data characteristics, and resource constraints.

Comparative Analysis of Aesthetic Judgment Between Orthodontists, General Dentists, and Different Versions of Large Language Models Using the IOTN-AC Index

OpenAsset: A Pipeline for Open-World Asset Integration into Indoor Scene Synthesis

This paper proposes OpenAsset, a novel framework that converts single images of real-world objects into reusable, canonicalized 3D assets that seamlessly integrate into the scene synthesis workflow and introduces an automated canonicalization module that normalizes the scale, orientation, and coordinate systems of the...

A Knowledge-Enhanced Iterative Reasoning Framework for Accurate and Traceable Fault Diagnosis in Distributed Service Systems

Fault diagnosis in distributed systems is challenged by complex service dependencies, cascading anomaly propagation, and similar symptom patterns. This paper proposes a knowledge-enhanced iterative reasoning framework that integrates large language models (LLMs) with a numerical domain knowledge graph (KG). The KG enco...