Results 121 to 130 of about 59,222 (317)

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Comparative Evaluation of Thresholding Methods for Optimized Digital Document Parsing Accuracy

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Automated parsing of semi-structured documents has become increasingly important, particularly in standardized formats like SATS-LN, which contain fixed-layout fields such as permit number, addresses, validity period, and item types.
Muhammad Noko Darpito, Kartika Firdausy, Abdul Fadlil   +2 more
doaj   +1 more source

A hybrid architecture for robust parsing of german

, 2002
This paper provides an overview of current research on a hybrid and robust parsing architecture for the morphological, syntactic and semantic annotation of German text corpora.
Erhard W. Hinrichs, Kübler, Sandra, Ra Kübler, Universität Tübingen, Müller, Frank H., Tylman Ule, Hinrichs, Erhard, Ule, Tylman, Frank H. Müller   +8 more
core  

Arabic parsing using grammar transforms [PDF]

, 2010
We investigate Arabic Context Free Grammar parsing with dependency annotation comparing lexicalised and unlexicalised parsers. We study how morphosyntactic as well as function tag information percolation in the form of grammar transforms (Johnson, 1998 ...
Tounsi, Lamia, van Genabith, Josef
core  

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Corpus Notarial y Sintáctico del Asturiano Medieval (CoNSAM-XIII)

Caracteres: Estudios Culturales y Críticos de la Esfera Digital, 2018
The Syntactic Notarial Corpus of Medieval Asturian (CoNSAM-XIII) is a syntactic repository made up of 50 notarial deeds from the 13th century, kept in the Oviedo Cathedral Archive and the Avilés Municipal Archive.
Rosabel San Segundo-Cachero
doaj  

Automatic evaluation of generation and parsing for machine translation with automatically acquired transfer rules [PDF]

, 2007
This paper presents a new method of evaluation for generation and parsing components of transfer-based MT systems where the transfer rules have been automatically acquired from parsed sentence-aligned bitext corpora.
Josef Van Genabith, Deirdre Hogan, Graham, Yvette, Hogan, Deirdre, Yvette Graham, van Genabith, Josef   +5 more
core  

Is it really that difficult to parse German?

, 2006
This paper presents a comparative study of probabilistic treebank parsing of German, using the Negra and TüBa-D/Z treebanks. Experiments with the Stanford parser, which uses a factored PCFG and dependency model, show that, contrary to previous claims for
Erhard W. Hinrichs, Kübler, Sandra, Wolfgang Maier, Hinrichs, Erhard, Sandra Kübler, Maier, Wolfgang   +5 more
core   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source