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pro vyhledávání: '"Williams, Jason D"'
Autor:
Sun, David Q., Abzaliev, Artem, Kotek, Hadas, Xiu, Zidi, Klein, Christopher, Williams, Jason D.
Controversy is a reflection of our zeitgeist, and an important aspect to any discourse. The rise of large language models (LLMs) as conversational systems has increased public reliance on these systems for answers to their various questions. Conseque
Externí odkaz:
http://arxiv.org/abs/2310.18130
Autor:
Aas, Cecilia, Abdelsalam, Hisham, Belousova, Irina, Bhargava, Shruti, Cheng, Jianpeng, Daland, Robert, Driesen, Joris, Flego, Federico, Guigue, Tristan, Johannsen, Anders, Lal, Partha, Lu, Jiarui, Moniz, Joel Ruben Antony, Perkins, Nathan, Piraviperumal, Dhivya, Pulman, Stephen, Séaghdha, Diarmuid Ó, Sun, David Q., Torr, John, Del Vecchio, Marco, Wacker, Jay, Williams, Jason D., Yu, Hong
It has recently become feasible to run personal digital assistants on phones and other personal devices. In this paper we describe a design for a natural language understanding system that runs on device. In comparison to a server-based assistant, th
Externí odkaz:
http://arxiv.org/abs/2308.03905
Autor:
Xiu, Zidi, Cheng, Kai-Chen, Sun, David Q., Lu, Jiannan, Kotek, Hadas, Zhang, Yuhan, McCarthy, Paul, Klein, Christopher, Pulman, Stephen, Williams, Jason D.
With the growing popularity of intelligent assistants (IAs), evaluating IA quality becomes an increasingly active field of research. This paper identifies and quantifies the feedback effect, a novel component in IA-user interactions: how the capabili
Externí odkaz:
http://arxiv.org/abs/2303.10255
Publikováno v:
In Current Opinion in Green and Sustainable Chemistry June 2024 47
Autor:
Sun, David Q., Kotek, Hadas, Klein, Christopher, Gupta, Mayank, Li, William, Williams, Jason D.
This paper develops and implements a scalable methodology for (a) estimating the noisiness of labels produced by a typical crowdsourcing semantic annotation task, and (b) reducing the resulting error of the labeling process by as much as 20-30% in co
Externí odkaz:
http://arxiv.org/abs/2012.04169
Autor:
Cheng, Jianpeng, Agrawal, Devang, Alonso, Hector Martinez, Bhargava, Shruti, Driesen, Joris, Flego, Federico, Ghosh, Shaona, Kaplan, Dain, Kartsaklis, Dimitri, Li, Lin, Piraviperumal, Dhivya, Williams, Jason D, Yu, Hong, Seaghdha, Diarmuid O, Johannsen, Anders
We consider a new perspective on dialog state tracking (DST), the task of estimating a user's goal through the course of a dialog. By formulating DST as a semantic parsing task over hierarchical representations, we can incorporate semantic compositio
Externí odkaz:
http://arxiv.org/abs/2010.12770
Autor:
Muralidharan, Deepak, Moniz, Joel Ruben Antony, Gao, Sida, Yang, Xiao, Kao, Justine, Pulman, Stephen, Kothari, Atish, Shen, Ray, Pan, Yinying, Kaul, Vivek, Ibrahim, Mubarak Seyed, Xiang, Gang, Dun, Nan, Zhou, Yidan, O, Andy, Zhang, Yuan, Chitkara, Pooja, Wang, Xuan, Patel, Alkesh, Tayal, Kushal, Zheng, Roger, Grasch, Peter, Williams, Jason D., Li, Lin
Named Entity Recognition (NER) and Entity Linking (EL) play an essential role in voice assistant interaction, but are challenging due to the special difficulties associated with spoken user queries. In this paper, we propose a novel architecture that
Externí odkaz:
http://arxiv.org/abs/2005.14408
Akademický článek
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Autor:
Chen, Xi C., Sagar, Adithya, Kao, Justine T., Li, Tony Y., Klein, Christopher, Pulman, Stephen, Garg, Ashish, Williams, Jason D.
We describe a method for selecting relevant new training data for the LSTM-based domain selection component of our personal assistant system. Adding more annotated training data for any ML system typically improves accuracy, but only if it provides e
Externí odkaz:
http://arxiv.org/abs/1908.11404
Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Text Adventure AI Competition, where it was evaluated on twenty unseen g
Externí odkaz:
http://arxiv.org/abs/1902.04259