Zobrazeno 1 - 10
of 120
pro vyhledávání: '"DENIS, PASCAL"'
Polysemy and synonymy are two crucial interrelated facets of lexical ambiguity. While both phenomena have been studied extensively in NLP, leading to dedicated systems, they are often been considered independently. While many tasks dealing with polys
Externí odkaz:
http://arxiv.org/abs/2406.20054
In this paper, we introduce a data augmentation approach specifically tailored to enhance intersectional fairness in classification tasks. Our method capitalizes on the hierarchical structure inherent to intersectionality, by viewing groups as inters
Externí odkaz:
http://arxiv.org/abs/2405.14521
Lexical Semantic Change is the study of how the meaning of words evolves through time. Another related question is whether and how lexical relations over pairs of words, such as synonymy, change over time. There are currently two competing, apparentl
Externí odkaz:
http://arxiv.org/abs/2305.19143
In this work, we consider the problem of intersectional group fairness in the classification setting, where the objective is to learn discrimination-free models in the presence of several intersecting sensitive groups. First, we illustrate various sh
Externí odkaz:
http://arxiv.org/abs/2305.12495
Publikováno v:
Conference of the European Chapter of the Association for Computational Linguistics, May 2023, Dubrovnik, Croatia
Recent work on predicting category structure with distributional models, using either static word embeddings (Heyman and Heyman, 2019) or contextualized language models (CLMs) (Misra et al., 2021), report low correlations with human ratings, thus cal
Externí odkaz:
http://arxiv.org/abs/2302.06942
Encoded text representations often capture sensitive attributes about individuals (e.g., race or gender), which raise privacy concerns and can make downstream models unfair to certain groups. In this work, we propose FEDERATE, an approach that combin
Externí odkaz:
http://arxiv.org/abs/2205.06135
Autor:
Denis, Pascal
Thesis (Ph. D.)--University of Texas at Austin, 2007.
Vita. Includes bibliographical references.
Vita. Includes bibliographical references.
Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a l
Externí odkaz:
http://arxiv.org/abs/1003.5372
Autor:
BOUVET, AURELIE, PAILLET, YOAN, ARCHAUX, FREDERIC, TILLON, LAURENT, DENIS, PASCAL, GILG, OLIVIER, GOSSELIN, FREDERIC
Publikováno v:
Environmental Conservation, 2016 Jun 01. 43(2), 148-160.
Externí odkaz:
https://www.jstor.org/stable/26320647
In this work, we tackle the problem of intersectional group fairness in the classification setting, where the objective is to learn discrimination-free models in the presence of several intersecting sensitive groups. First, we illustrate various shor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e78f9d6c4d5052746c367c89b5017f0
http://arxiv.org/abs/2305.12495
http://arxiv.org/abs/2305.12495