large language models

Can LLM Code Explanations Adapt to Diverse Problem-Solvers' Needs?

This paper is the first to investigate problem-solving style adaptations in LLM code explanation, contributing two problem-solving adaptation approaches: declarative statements for each adaptation and 10 problem-solving style prompts.

Just Talk Once: Communication-Efficient Split Federated LLM Fine-Tuning on Edge Devices

L-shaped SFT is presented, a split fine-tuning framework that removes the need for continuous client participation and introduces one-shot SFT, in which clients upload activations once and then go offline while the server continues optimization over cached representations.

Longitudinal Data from a Large, Multi-Target Stool DNA Colorectal Cancer Screening Program

Background & Aims: Multi-target stool DNA (mt-sDNA) is an established stool-based colorectal cancer screening test, yet long-term performance is not well-described. We evaluated follow-up colonoscopy rates & quality, neoplasia yield, and repeat-testing adherence over 10 years with an integrated screening program. Metho...

Digital linguistic sovereignty and Kazakh language policy in the digital environment

This article examines the impact of the digital environment on the status and place of language. The focus is on the concept of digital linguistic sovereignty, understood as a nation’s ability to ensure the functional competitiveness of the language in the age of artificial intelligence and big data. In this regard, Ka...

Towards Self-Developing ERP: Operating Enterprise Resource Planning with Large Language Models - Source Code Release

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Closed-Domain Event Extraction Literature Review

Executive Summary This work is a literature review on the task of closed-domain event extraction, a task within natural language processing (NLP) where the goal is to detect the presence of an event (an occurrence of an action or state change) and event-related information (known as arguments) and to return the event s...

A Review of Neural Question Generation: Approaches, Challenges, and Future Directions

This survey provides a comprehensive review of developments in NQG, spanning traditional neural approaches to the latest paradigms driven by large language models (LLMs) and multimodal large language models (MLLMs).

PALRec: Large Language Model-Based Sequential Recommendation with Parameter-Preserving Augmentation

PALRec is proposed, a parameter-preserving augmentation framework that equips an LLM with recommendation capabilities while keeping its original parameters fixed and consistently outperforms fully fine-tuned counterparts in recommendation accuracy while preserving the LLM’s pre-trained knowledge.

Atlantis: An integrative database for human proteome structural and functional sites

Atlantis, a database that integrates structural and functional information at the human proteome residue level and a Model Context Protocol (MCP) connector allows the interrogation of the resource through Large Language Models (LLMs) or agentic frameworks for biomedical research.

A domain-specific lightweight GPT model for instructor feedback generation in air traffic control training

Transforming Physical Education and Sport Sciences Education in the Age of Smartification: A Narrative–Analytical Review of Technologies, Applications, Opportunities, and Challenges

The expansion of smart technologies has transformed teaching and learning paradigms in physical education and sport sciences, paving the way for interactive, data-driven, and personalized instruction. Objective: This study aimed to examine the role of smart technologies in transforming physical education instruction an...

zksdu/llm-acmg-variant-audit: v1.1.0 — manuscript submission version

Companion code and data for "Multi-vendor evaluation of large language models for ACMG/AMP variant classification with controlled data contamination" (Journal of Genetics and Genomics). 9 LLMs × 5,000 temporally-blinded ClinVar variants (45,000 evaluations), with sub-experiments on allele-frequency ablation, conflictin...