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pro vyhledávání: '"Dai, Luke"'
Autor:
Shi, Hangjie, Ball, Leslie, Thattai, Govind, Zhang, Desheng, Hu, Lucy, Gao, Qiaozi, Shakiah, Suhaila, Gao, Xiaofeng, Padmakumar, Aishwarya, Yang, Bofei, Chung, Cadence, Guthy, Dinakar, Sukhatme, Gaurav, Arumugam, Karthika, Wen, Matthew, Ipek, Osman, Lange, Patrick, Khanna, Rohan, Pansare, Shreyas, Sharma, Vasu, Zhang, Chao, Flagg, Cris, Pressel, Daniel, Vaz, Lavina, Dai, Luke, Goyal, Prasoon, Sahai, Sattvik, Liu, Shaohua, Lu, Yao, Gottardi, Anna, Hu, Shui, Liu, Yang, Hakkani-Tur, Dilek, Bland, Kate, Rocker, Heather, Jeun, James, Rao, Yadunandana, Johnston, Michael, Iyengar, Akshaya, Mandal, Arindam, Natarajan, Prem, Ghanadan, Reza
The Alexa Prize program has empowered numerous university students to explore, experiment, and showcase their talents in building conversational agents through challenges like the SocialBot Grand Challenge and the TaskBot Challenge. As conversational
Externí odkaz:
http://arxiv.org/abs/2308.05221
Effective evaluation methods remain a significant challenge for research on open-domain conversational dialogue systems. Explicit satisfaction ratings can be elicited from users, but users often do not provide ratings when asked, and those they give
Externí odkaz:
http://arxiv.org/abs/2301.13372
Autor:
Gottardi, Anna, Ipek, Osman, Castellucci, Giuseppe, Hu, Shui, Vaz, Lavina, Lu, Yao, Khatri, Anju, Chadha, Anjali, Zhang, Desheng, Sahai, Sattvik, Dwivedi, Prerna, Shi, Hangjie, Hu, Lucy, Huang, Andy, Dai, Luke, Yang, Bofei, Somani, Varun, Rajan, Pankaj, Rezac, Ron, Johnston, Michael, Stiff, Savanna, Ball, Leslie, Carmel, David, Liu, Yang, Hakkani-Tur, Dilek, Rokhlenko, Oleg, Bland, Kate, Agichtein, Eugene, Ghanadan, Reza, Maarek, Yoelle
Since its inception in 2016, the Alexa Prize program has enabled hundreds of university students to explore and compete to develop conversational agents through the SocialBot Grand Challenge. The goal of the challenge is to build agents capable of co
Externí odkaz:
http://arxiv.org/abs/2209.06321
Publikováno v:
Association for Computational Linguistics (2021)
The Shuffle Test is the most common task to evaluate whether NLP models can measure coherence in text. Most recent work uses direct supervision on the task; we show that by simply finetuning a RoBERTa model, we can achieve a near perfect accuracy of
Externí odkaz:
http://arxiv.org/abs/2107.03448
Akademický článek
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