Results 21 to 30 of about 109,600 (254)

Comparison of Language Models in Skills Extraction From Vacancies and Resumes

Современные информационные технологии и IT-образование
The ability of large language models (LLMs) to “understand” large volumes of text data allows for consistent quality selection of candidates for company openings.
Lyubov Komarova, Vladimir Soloviev, Alexey Kolosov   +2 more
doaj   +1 more source

LLM-enhanced space-air-ground-sea integrated networks

The space-air-ground-sea integrated networking (SAGSIN) concept promises seamless global multimedia connectivity, yet two obstacles still limit its practical deployment.
Halvin Yang (18393345), Mahsa Derakhshani (2572993), Sangarapillai Lambotharan (1252278), Lajos Hanzo (7211693)   +3 more
core   +5 more sources

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

LLM questions papers - 2016

, 2016
LLM questions paper ...
Vidyasagar University
core   +1 more source

Imaginer avec ChatGPT : autour de la Muraille de Chine

Interfaces Numériques
Entre le 18 et le 20 janvier 2024, l’écrivaine Milène Tournier fait paraître sur sa page Facebook une série de posts qui reproduisent l’expérience d’écriture qu’elle mène simultanément avec ChatGPT 3.5. « Bonjour.
Marine RIGUET
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science

Advanced Engineering Materials, EarlyView.
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Parallelism strategies as a key factor for deploying Large Language Models on consumer gpus

Системный анализ и прикладная информатика
The exponential growth in the size of Large Language Models (LLMs) creates significant barriers to their local deployment, primarily due to Video RAM (VRAM) shortages on single devices.
K. S. Kurochka, Yu. S. Basharymau, Yu. D. Youzhanka   +2 more
doaj   +1 more source