Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Tommaso Fornaciari"'
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
instname
[EN] Identifying deceptive online reviews is a challenging tasks for Natural Language Processing (NLP). Collecting corpora for the task is difficult, because normally it is not possible to know whether reviews are genuine. A common workaround involve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::525b82eb6d21e80311bceffb5a62ddce
https://doi.org/10.1007/s10579-020-09486-5
https://doi.org/10.1007/s10579-020-09486-5
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15ab9f19712dcbbf76c56b8fbcf8d7d5
https://doi.org/10.18653/v1/2022.acl-demo.12
https://doi.org/10.18653/v1/2022.acl-demo.12
Publikováno v:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Fornaciari, T, Uma, A, Paun, S, Plank, B, Hovy, D & Poesio, M 2021, Beyond Black & White: Leveraging Annotator Disagreement via Soft-Label Multi-Task Learning . in Proceedings of NAACL . Association for Computational Linguistics, pp. 2591–2597 .
NAACL-HLT
Fornaciari, T, Uma, A, Paun, S, Plank, B, Hovy, D & Poesio, M 2021, Beyond Black & White: Leveraging Annotator Disagreement via Soft-Label Multi-Task Learning . in Proceedings of NAACL . Association for Computational Linguistics, pp. 2591–2597 .
NAACL-HLT
Supervised learning assumes that a ground truth label exists. However, the reliability of this ground truth depends on human annotators, who often disagree. Prior work has shown that this disagreement can be helpful in training models. We propose a n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86a09e55737fbf08b689aa3eb596b558
Autor:
Jon Chamberlain, Tommaso Fornaciari, Massimo Poesio, Barbara Plank, Anca Dumitrache, Alexandra Uma, Edwin Simpson, Tristan Miller
Publikováno v:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
SemEval@ACL/IJCNLP
SemEval@ACL/IJCNLP
Disagreement between coders is ubiquitous in virtually all datasets annotated with human judgements in both natural language processing and computer vision. However, most supervised machine learning methods assume that a single preferred interpretati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::078f73efdbc14817a65a982271e72d84
Publikováno v:
ACL/IJCNLP (Findings)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0bdea956be42414a0f2cf35ea25e433
https://doi.org/10.18653/v1/2021.findings-acl.301
https://doi.org/10.18653/v1/2021.findings-acl.301
Publikováno v:
EACL
Scopus-Elsevier
Scopus-Elsevier
Spotting a lie is challenging but has an enormous potential impact on security as well as private and public safety. Several NLP methods have been proposed to classify texts as truthful or deceptive. In most cases, however, the target texts' precedin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5170bdf746be6e49809638b22a1ad0f9
https://doi.org/10.18653/v1/2021.eacl-main.232
https://doi.org/10.18653/v1/2021.eacl-main.232
Publikováno v:
Journal of Artificial Intelligence Research
Many tasks in Natural Language Processing (NLP) and Computer Vision (CV) offer evidence that humans disagree, from objective tasks such as part-of-speech tagging to more subjective tasks such as classifying an image or deciding whether a proposition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b1e663b2e251dccf61dc2b7afa4b113
https://hdl.handle.net/11565/4051365
https://hdl.handle.net/11565/4051365
Autor:
Silviu Paun, Dirk Hovy, Tommaso Fornaciari, Alexandra Uma, Barbara Plank, Michael Fell, Massimo Poesio, Valerio Basile
Publikováno v:
Proceedings of the 1st Workshop on Benchmarking: Past, Present and Future
Basile, V, Fell, M, Fornaciari, T, Hovy, D, Paun, S, Plank, B, Poesio, M & Uma, A 2021, We Need to Consider Disagreement in Evaluation . in ACL-IJCNLP2021 Workshop on Benchmarking: Past, Present and Future . Association for Computational Linguistics, pp. 15-21 . https://doi.org/10.18653/v1/2021.bppf-1.3
Basile, V, Fell, M, Fornaciari, T, Hovy, D, Paun, S, Plank, B, Poesio, M & Uma, A 2021, We Need to Consider Disagreement in Evaluation . in ACL-IJCNLP2021 Workshop on Benchmarking: Past, Present and Future . Association for Computational Linguistics, pp. 15-21 . https://doi.org/10.18653/v1/2021.bppf-1.3
Evaluation is of paramount importance in data- driven research fields such as Natural Language Processing (NLP) and Computer Vision (CV). But current evaluation practice in NLP, except for end-to-end tasks such as machine translation, spoken dialogue
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf9f871b2d3b1d1cfeec4726cd45ab4e
https://doi.org/10.18653/v1/2021.bppf-1.3
https://doi.org/10.18653/v1/2021.bppf-1.3
Publikováno v:
EMNLP (Findings)
Scopus-Elsevier
Scopus-Elsevier
When interacting with each other, we motivate, advise, inform, show love or power towards our peers. However, the way we interact may also hold some indication on how successful we are, as people often try to help each other to achieve their goals. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48c79b2805adfb42a1123a759ac2c46c
https://doi.org/10.18653/v1/2020.findings-emnlp.214
https://doi.org/10.18653/v1/2020.findings-emnlp.214
Autor:
Fernando Vega-Redondo, Paolo Pin, Diego Ubfal, Cristiana Benedetti-Fasil, Charles Brummitt, Gaia Rubera, Dirk Hovy, Tommaso Fornaciari
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::944e58adc9a659c13e25efa16f464883
https://doi.org/10.2139/ssrn.3513690
https://doi.org/10.2139/ssrn.3513690