Results 101 to 110 of about 499,146 (320)
Comparison of Language Models for English-Latvian Semantic Search
Applied Computer SystemsIn this study, ten language models are explored and compared in an English-Latvian semantic information retrieval setting, where the indexed collection of documents is written in English while the query documents are written in Latvian.
Kucheravy Artem, Jēkabsons Gints
doaj +1 more source
Open Computer Science, 2019 Modern search is heavily powered by knowledge bases, but users still query using keywords or natural language. As search becomes increasingly dependent on the integration of text and knowledge, novel approaches for a unified representation of combined ...
Devezas José, Nunes Sérgio
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Personalized Fuzzy Text Search Using Interest Prediction and Word Vectorization
, 2017 In this paper we study the personalized text search problem. The keyword based search method in conventional algorithms has a low efficiency in understanding users' intention since the semantic meaning, user profile, user interests are not always ...
Gao, Tianmeng +3 more
core
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
, 2017 Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself.
Guu, Kelvin +3 more
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BeamAttack: Generating High-quality Textual Adversarial Examples through Beam Search and Mixed Semantic Spaces [PDF]
, 2023 Hai Zhu, Qinyang Zhao, Yuren Wu
openalex +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
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 +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan +8 more
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Mokslas: Lietuvos Ateitis, 2014 The paper presents investigation on search in electronic catalogues. The chosen problem domain is the search system in the electronic catalogue of Lithuanian Academic Libraries. The catalogue uses ALEPH system with MARC21 bibliographic format.
Titas Savickas
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Large Language Model‐Based Chatbots in Higher Education
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source