Zobrazeno 1 - 10
of 1 044
pro vyhledávání: '"Knight, Kevin"'
Early disease detection in veterinary care relies on identifying subclinical abnormalities in asymptomatic animals during wellness visits. This study introduces an algorithm designed to distinguish between wellness and other veterinary visits.The pur
Externí odkaz:
http://arxiv.org/abs/2406.10314
Autor:
Arkhangorodsky, Arkady, Fang, Scot, Knight, Victoria, Nagesh, Ajay, Ryskina, Maria, Knight, Kevin
Task-oriented dialog systems are often trained on human/human dialogs, such as collected from Wizard-of-Oz interfaces. However, human/human corpora are frequently too small for supervised training to be effective. This paper investigates two approach
Externí odkaz:
http://arxiv.org/abs/2109.09597
Autor:
Arkhangorodsky, Arkady, Chu, Christopher, Fang, Scot, Huang, Yiqi, Jiang, Denglin, Nagesh, Ajay, Zhang, Boliang, Knight, Kevin
We present MeetDot, a videoconferencing system with live translation captions overlaid on screen. The system aims to facilitate conversation between people who speak different languages, thereby reducing communication barriers between multilingual pa
Externí odkaz:
http://arxiv.org/abs/2109.09577
Autor:
Ryskina, Maria, Knight, Kevin
Embedding words in high-dimensional vector spaces has proven valuable in many natural language applications. In this work, we investigate whether similarly-trained embeddings of integers can capture concepts that are useful for mathematical applicati
Externí odkaz:
http://arxiv.org/abs/2109.07230
This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9). Participants in the shared task build an end-to-end task completion dialog system which is
Externí odkaz:
http://arxiv.org/abs/2102.04506
We investigate why neural machine translation (NMT) systems assign high probability to empty translations. We find two explanations. First, label smoothing makes correct-length translations less confident, making it easier for the empty translation t
Externí odkaz:
http://arxiv.org/abs/2012.13454
We propose a novel approach, MUSE, to illustrate textual attributes visually via portrait generation. MUSE takes a set of attributes written in text, in addition to facial features extracted from a photo of the subject as input. We propose 11 attribu
Externí odkaz:
http://arxiv.org/abs/2011.04761