Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Venelin Kovatchev"'
Publikováno v:
Psychological Assessment. 35:165-177
Autor:
Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahadiran, Simon Mille, Ashish Shrivastava, Samson Tan, null Tongshang Wu, Jascha Sohl-Dickstein, Jinho Choi, Eduard Hovy, Ondřej Dušek, Sebastian Ruder, Sajant Anand, Nagender Aneja, Rabin Banjade, Lisa Barthe, Hanna Behnke, Ian Berlot-Attwell, Connor Boyle, Caroline Brun, Marco Antonio Sobrevilla Cabezudo, Samuel Cahyawijaya, Emile Chapuis, Wanxiang Che, Mukund Choudhary, Christian Clauss, Pierre Colombo, Filip Cornell, Gautier Dagan, Mayukh Das, Tanay Dixit, Thomas Dopierre, Paul-Alexis Dray, Suchitra Dubey, Tatiana Ekeinhor, Marco Di Giovanni, Tanya Goyal, Rishabh Gupta, Louanes Hamla, Sang Han, Fabrice Harel-Canada, Antoine Honoré, Ishan Jindal, Przemysław Joniak, Denis Kleyko, Venelin Kovatchev, Kalpesh Krishna, Ashutosh Kumar, Stefan Langer, Seungjae Ryan Lee, Corey James Levinson, Hualou Liang, Kaizhao Liang, Zhexiong Liu, Andrey Lukyanenko, Vukosi Marivate, Gerard De Melo, Simon Meoni, Maxine Meyer, Afnan Mir, Nafise Sadat Moosavi, Niklas Meunnighoff, Timothy Sum Hon Mun, Kenton Murray, Marcin Namysl, Maria Obedkova, Priti Oli, Nivranshu Pasricha, Jan Pfister, Richard Plant, Vinay Prabhu, Vasile Pais, Libo Qin, Shahab Raji, Pawan Kumar Rajpoot, Vikas Raunak, Roy Rinberg, Nicholas Roberts, Juan Diego Rodriguez, Claude Roux, Vasconcellos Samus, Ananya Sai, Robin Schmidt, Thomas Scialom, Tshephisho Sefara, Saqib Shamsi, Xudong Shen, Yiwen Shi, Haoyue Shi, Anna Shvets, Nick Siegel, Damien Sileo, Jamie Simon, Chandan Singh, Roman Sitelew, Priyank Soni, Taylor Sorensen, William Soto, Aman Srivastava, Aditya Srivatsa, Tony Sun, Mukund Varma, A Tabassum, Fiona Tan, Ryan Teehan, Mo Tiwari, Marie Tolkiehn, Athena Wang, Zijian Wang, Zijie Wang, Gloria Wang, Fuxuan Wei, Bryan Wilie, Genta Indra Winata, Xinyu Wu, Witold Wydmanski, Tianbao Xie, Usama Yaseen, Michael Yee, Jing Zhang, Yue Zhang
Publikováno v:
Northern European Journal of Language Technology. 9
Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural lang
Misinformation threatens modern society by promoting distrust in science, changing narratives in public health, heightening social polarization, and disrupting democratic elections and financial markets, among a myriad of other societal harms. To add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9756b2935437facd85a43648904bc17
http://arxiv.org/abs/2301.03056
http://arxiv.org/abs/2301.03056
Publikováno v:
ACL/IJCNLP (1)
Scopus-Elsevier
Scopus-Elsevier
In this paper we implement and compare 7 different data augmentation strategies for the task of automatic scoring of children's ability to understand others' thoughts, feelings, and desires (or "mindreading"). We recruit in-domain experts to re-annot
Autor:
Eduardo Blanco, Elizabeth Wei, Pranoy Dutta, Venelin Kovatchev, Mosharaf Hossain, Tiffany Kao
Publikováno v:
EMNLP (1)
Negation is underrepresented in existing natural language inference benchmarks. Additionally, one can often ignore the few negations in existing benchmarks and still make the right inference judgments. In this paper, we present a new benchmark for na
Publikováno v:
RANLP
In this paper, we present a new approach for the evaluation, error analysis, and interpretation of supervised and unsupervised Paraphrase Identification (PI) systems. Our evaluation framework makes use of a PI corpus annotated with linguistic phenome
Publikováno v:
Dipòsit Digital de la UB
Universidad de Barcelona
Universidad de Barcelona
One of the goals in Cognitive Linguistics is the automatic identification and analysis of constructions, since they are fundamental linguistic units for understanding language. This article presents DISCOver, an unsupervised methodology for the autom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e84d56f3610534d293084263d525585d
http://hdl.handle.net/2445/171321
http://hdl.handle.net/2445/171321
Publikováno v:
LAW@ACL
Pairs of sentences, phrases, or other text pieces can hold semantic relations such as paraphrasing, textual entailment, contradiction, specificity, and semantic similarity. These relations are usually studied in isolation and no dataset exists where
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83646e10f61bdf6ed93fdf38eee76be7
https://duepublico2.uni-due.de/receive/duepublico_mods_00072062
https://duepublico2.uni-due.de/receive/duepublico_mods_00072062