large language models

Generative AI as a Creative Paradigm in Marketing Communication

Generative artificial intelligence is redefining marketing communication by extending the discipline beyond human-driven creativity into a data-supported, emotionally responsive, and context-aware domain. Unlike traditional AI focused on automation and analytics, generative AI enables personalized content creation, imm...

"O'ZBEK VA TURK TILLARIDA AVTOMATIK MORFOLOGIK TAHLIL VA LEMMATIZATSIYA: MASHINA TARJIMASI UCHUN ZAMONAVIY YONDASHUVLAR"

This article analyzes contemporary approaches to automatic morphological analysis and lemmatization in the Uzbek and Turkish languages, which have an agglutinative structure. It also highlights major linguistic challenges characteristic of these languages, including the large number of word forms (vocabulary explosion)...

Dataset for "A flexible language model-assisted electronic design automation framework"

This dataset relates to the manuscript "A flexible language model-assisted electronic design automation framework" authored by Cristian Sestito, Panagiota Kontou, Pratibha Verma, Atish Dixit, Alexandros D. Keros, Michael O'Boyle, Christos-Savvas Bouganis, and Themis Prodromakis, accepted for publication in Scientific R...

Coarse-to-Fine Label Distribution Learning for High-Cardinality Survey Simulation

Modeling fine-grained survey distributions for high-cardinality large language model prediction is challenging under mixed-cardinality supervision. Because low-cardinality surveys dominate training, standard label distribution learning (LDL) develops positional bias toward early response regions and fails to generalize...

Research on solid-state battery information mining based on large language models and chain-of-thought reasoning

Solid-state batteries (SSBs) represent a next-generation energy storage technology. However, the wide diversity of solid-state electrolyte (SSE) chemistries, coupled with the complexity of their synthesis and processing routes, makes systematic investigation, knowledge reuse, and database construction particularly chal...

Automating the triage of rheumatology outpatient referrals: a comparative evaluation of 23 large language models under simple and advanced prompting

Abstract Triage of rheumatology outpatient referrals is a high-volume administrative task that consumes senior specialist time without advancing patient care. The human triage system is only moderately accurate and reproducible. We assessed whether contemporary large language models (LLMs) are able to perform well enou...

Towards UVL-Based Variability Modelling of Drone Propellers

Beyond Emotion Scores: Reproducibility Data and Validation Materials for a Systematic Review of Emotional AI (2019–2026)

This dataset provides the supplementary data and reproducibility materials accompanying the systematic literature review Beyond Emotion Scores: Evaluating Emotional AI Across Benchmarks, Cultures, and Time in the LLM Era - A Systematic Review. The review covers literature published from 1 January 2019 to 26 September 2...

Prognostic Utility and Clinical Impact of Soluble Urokinase Plasminogen Activator Receptor in Adult Emergency and Acute-Care Patients: A Systematic Review and Narrative Synthesis

Soluble urokinase plasminogen activator receptor (suPAR) reflects systemic immune activation and biological vulnerability and has been proposed as a cross-diagnostic prognostic biomarker in emergency care. We systematically reviewed full-text English-language reports published from 1 January 2015 through 20 July 2026 i...

Self-Reflection and Error-Correction Mechanisms in LLMs Driven by Reinforcement Learning

Large language models have shown very strong abilities on complex reason work, but they still have many problems, these problems include error accumulation and hallucinations. Therefore, letting these models have the ability of self-reflection and error correction has hence become a core research focus. This research p...

GeoAct: evaluation materials for action-level access control in a geospatial LLM agent

Evaluation materials for the paper "GeoAct: action-level access control for agentic geospatial analysis with local large language models". GeoAct is a geospatial agent that plans and executes spatial-analysis tool calls on behalf of a user in a multi-tenant spatial data infrastructure. Every tool invocation is authoris...

A large-scale pipeline for LLM-assisted corpus annotation

As natural language corpora expand at an unprecedented rate, manual annotation remains a significant methodological bottleneck in corpus linguistic work. We address this challenge by presenting a scalable pipeline for automating grammatical annotation using large language models (LLMs). We demonstrate the pipeli...