Results 241 to 250 of about 368,749 (284)

Revolutionizing dermatopathology using AI in skin diagnostics: scoping review. [PDF]

Front Med (Lausanne)
Rammal R, Mohy U Din A, Alam T.
europepmc   +1 more source

Evaluating reasoning large language models on rumor generation, detection, and debunking tasks. [PDF]

iScience
Hu Y, Tian X.
europepmc   +1 more source

Polytope: High-resolution epitope barcoding for in vivo spatial fate-mapping

Postrach D, Pritchard CEJ, Frank L, van Leeuwen T, Messal HA, Krimpenfort P, van Rheenen J, Rodewald H.   +7 more
europepmc   +1 more source

A STUDY OF TEXTUAL ENTAILMENT

International Journal on Artificial Intelligence Tools, 2008
In this paper we study a graph-based approach to the task of Recognizing Textual Entailment between a Text and a Hypothesis. The approach takes into account the full lexico-syntactic context of both the Text and Hypothesis and is based on the concept of subsumption.
Vasile Rus, Philip M. McCarthy, Danielle S. McNamara, Arthur C. Graesser   +3 more
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A Linguistic Inspection of Textual Entailment

, 2005
Recognition of textual entailment is not an easy task. In fact, early experimental evidences in [1] seems to demonstrate that even human judges often fail in reaching an agreement on the existence of entailment relation between two expressions.
PAZIENZA, MARIA TERESA, Pennacchiotti, M, ZANZOTTO, FABIO MASSIMO   +2 more
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A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment

International Journal of Machine Learning and Cybernetics, 2011
In this paper we explain how to build a recognizing textual entailment (RTE) system which only uses semantic similarity measures based on WordNet. We show how the widely used WordNet-based semantic measures can be generalized to build sentence level semantic metrics in order to be used in both mono-lingual and cross-lingual textual entailment.
exaly   +3 more sources

Entailment analysis for improving Chinese textual entailment system

2013 IEEE 14th International Conference on Information Reuse & Integration (IRI), 2013
Textual Entailment (TE) is a critical issue in natural language processing (NLP); many NLP applications can be benefited from the recognition of textual entailment (RTE). In this paper we report our observation on how to improve the Chinese textual entailment system and the experiment results on the NTCIR-10 RITE-2 dataset.
Shih-Hung Wu
exaly   +3 more sources

Paraphrase and Textual Entailment Generation

Lecture Notes in Computer Science, 2014
One particular information can be conveyed by many different sentences. This variety concerns the choice of vocabulary and style as well as the level of detail (from laconism or succinctness to total verbosity). Although verbosity in written texts is considered bad style, generated verbosity can help natural language processing (NLP) systems to fill in
exaly   +3 more sources

Textual entailment graphs

Natural Language Engineering, 2015
AbstractIn this work, we present a novel type of graphs for natural language processing (NLP), namely textual entailment graphs (TEGs). We describe the complete methodology we developed for the construction of such graphs and provide some baselines for this task by evaluating relevant state-of-the-art technology.
Lili Kotlerman, Ido Dagan, Bernardo Magnini, Luisa Bentivogli   +3 more
openaire   +3 more sources