Results 71 to 80 of about 8,049,290 (285)
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Enhancing the Interpretability of NLI Models Using LLMs and Active Learning Algorithms
In the field of Natural Language Inference (NLI), model interpretability remains an urgent and unresolved challenge. Existing interpretability-oriented annotated datasets are highly limited, and manually constructing natural language explanations is both
Qi Wang, Junqiang Liu
doaj +1 more source
Presupposed content and entailments in natural language inference [PDF]
Previous work has presented an accurate natural logic model for natural language inference. Other work has demonstrated the effectiveness of computing presuppositions for solving natural language inference problems. We extend this work to create a system for correctly computing lexical presuppositions and their interactions within the natural logic ...
David Clausen, Christopher D. Manning
openaire +2 more sources
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 +3 more
wiley +1 more source
Simpful: A User-Friendly Python Library for Fuzzy Logic
Many researchers have used fuzzy set theory and fuzzy logic in a variety of applications related to computer science and engineering, given the capability of fuzzy inference systems to deal with uncertainty, represent vague concepts, and connect human ...
Simone Spolaor +5 more
doaj +1 more source
Pushing the boundary on Natural Language Inference
Natural Language Inference (NLI) is a central task in natural language understanding with applications in fact-checking, question answering, and information retrieval. Despite its importance, current NLI systems heavily rely on supervised learning with datasets that often contain annotation artifacts and biases, limiting generalization and real-world ...
Pablo Miralles-González +3 more
openaire +2 more sources
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 +5 more
wiley +1 more source
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 +10 more
wiley +1 more source
Enhancing alignment with context similarity for natural language inference
Previous approaches generally use context information to improve the word representation but ignore the importance of context similarity in aligning tokens.Furthermore,most of them uniformly weight various local decisions during aggregation for the ...
Qianlong DU, Chengqing ZONG, Keh-Yih SU
doaj
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source

