Zobrazeno 1 - 5
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pro vyhledávání: '"Rubino, Melanie"'
Autor:
Arkoudas, Konstantine, Mesnards, Nicolas Guenon des, Rubino, Melanie, Swamy, Sandesh, Khanna, Saarthak, Sun, Weiqi, Haidar, Khan
Much recent work in task-oriented parsing has focused on finding a middle ground between flat slots and intents, which are inexpressive but easy to annotate, and powerful representations such as the lambda calculus, which are expressive but costly to
Externí odkaz:
http://arxiv.org/abs/2212.00265
Autor:
Rubino, Melanie, Mesnards, Nicolas Guenon des, Shah, Uday, Jiang, Nanjiang, Sun, Weiqi, Arkoudas, Konstantine
Deep learning methods have enabled task-oriented semantic parsing of increasingly complex utterances. However, a single model is still typically trained and deployed for each task separately, requiring labeled training data for each, which makes it c
Externí odkaz:
http://arxiv.org/abs/2206.05352
Semantic parsing is an important NLP problem, particularly for voice assistants such as Alexa and Google Assistant. State-of-the-art (SOTA) semantic parsers are seq2seq architectures based on large language models that have been pretrained on vast am
Externí odkaz:
http://arxiv.org/abs/2204.14243
Autor:
Sun, Weiqi, Khan, Haidar, Mesnards, Nicolas Guenon des, Rubino, Melanie, Arkoudas, Konstantine
Semantic parsing is a key NLP task that maps natural language to structured meaning representations. As in many other NLP tasks, SOTA performance in semantic parsing is now attained by fine-tuning a large pretrained language model (PLM). While effect
Externí odkaz:
http://arxiv.org/abs/2203.02652
Autor:
Rubino, Melanie1 mrubino@wolve.com, Ata, Barış2 b-ata@kellogg.northwestern.edu
Publikováno v:
Operations Research. Jan/Feb2009, Vol. 57 Issue 1, p94-108. 15p. 2 Diagrams, 3 Charts, 6 Graphs.