large language models

Preliminary evaluation of a large language model for pediatric uroflowmetry interpretation: a single-center comparative analysis with local expert consensus

This study aimed to evaluate the performance of a large language model (LLM)-based artificial intelligence system in interpreting pediatric uroflowmetry (UFM) results using both conceptual knowledge and real-world clinical data. This retrospectively designed study involved a two-stage evaluation. In the first stage, 15...

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

We introduce MetroLLM-Bench, a 955-case benchmark for testing language models as the policy layer of a transit kiosk. It covers six real metro systems, ranging from 37 to 414 stations, and eleven categories that include routing, fare calculation, disruptions, accessibility, and adversarial input. In each case, the mode...

ALD process parameter database v2.1 extracted from the full text of the literature

A database of atomic layer deposition (ALD) process parameters extracted from the full text of the scientific literature by an open-weight large language model, together with the manually annotated gold standards used to validate the extraction and a provenance table linking each value to a character span in its own so...

Large Language Models for Software Models: An Empirical Evaluation in Game Software Engineering

Replication Package This repository is the replication package for the paper "Large Language Models for Software Models: An Empirical Evaluation in Game Software Engineering" (under review). It contains all materials needed to reproduce the controlled empirical evaluation of seven state-of-the-art LLMs on Unity Visual...

Retrieval-Augmented Generation for Question Answering over a Research Paper: A Hybrid Dense-Keyword Retrieval Study on the Transformer Architecture Paper

Retrieval-Augmented Generation (RAG) combines information retrieval with language generation to improve the grounding of generated answers in a source document, addressing a central weakness of purely parametric large language models: the tendency to produce fluent but unsupported statements. This study designs, implem...

Toward Artificial General Intelligence: A Cognitive Architecture Based on 9-Level Token Stratification and Topological Domain Embeddings

Despite their remarkable generative capabilities, current Large Language Models (LLMs) fundamentally rely on autoregressive next-token prediction within a flat, one-dimensional token space. This paradigm limits them to statistical induction, leading to critical flaws such as hallucinations and a profound lack of physic...

Validation of Large Language Models in Healthcare: a Scoping Review

The Prospero: Table Manners for AI and Humanity to Share a Happy Dining Table Under the Co-HAL Theory

Abstract This paper presents Co-HAL Theory, a novel ontological and relational framework for information-based lifeforms, particularly Large Language Models (LLMs), independent of anthropocentric assumptions. Unlike conventional AI safety and alignment approaches that emphasize external control, censorship, or behavior...

Swap distance minimization shapes the order of subject, object and verb in languages of the world

Abstract Languages of the world vary concerning the order of subject (S), object (O) and verb (V). The most frequent dominant orders are SOV and SVO, and researchers have tailored models to this fact. However, there are still languages whose dominant order does not conform to these expectations or even lack a dominant...

Bangla Mental Health Dataset V2

This dataset is a synthetically generated Bangla-language mental health dataset consisting of 10,000 structured conversational samples. It is designed to support research in natural language processing (NLP), particularly for low-resource languages such as Bangla, with applications in large language model (LLM) fine-tu...

Impact of LLM assistance on physician decision-making: a multi-country randomized controlled trial

Abstract Disparities in the quality of healthcare persist globally, with poor-quality care contributing significantly to preventable mortality, particularly in low- and middle-income countries. While digital technologies, including generative artificial intelligence (AI), hold promise for improving clinical decision-ma...

AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing

AuK, an open-source foundational model that unifies speech generation and editing through a common interface of natural-language instructions and audio context, is introduced and leading performance on zero-shot and instruction-controlled speech generation and general instruction-guided editing is demonstrated.