4 citations · 6 across the 5 of their papers we have counts for
5 papers
Controlled Decoding from Language Models
Sidharth Mudgal, Jong Lee, Harish Ganapathy +10
KL-regularized reinforcement learning (RL) is a popular alignment framework to control the language model responses towards high reward outcomes. We pose a tokenwise RL objective a…
Using Machine Translation to Localize Task Oriented NLG Output
Scott Roy, Cliff Brunk, Kyu-Young Kim +6
One of the challenges in a task oriented natural language application like the Google Assistant, Siri, or Alexa is to localize the output to many languages. This paper explores doi…
A scalable framework for learning from implicit user feedback to improve natural language understanding in large-scale conversational AI systems
Sunghyun Park, Han Li, Ameen Patel +5
Natural Language Understanding (NLU) is an established component within a conversational AI or digital assistant system, and it is responsible for producing semantic understanding…
Continuous Learning for Large-scale Personalized Domain Classification
Han Li, Jihwan Lee, Sidharth Mudgal +2
Domain classification is the task of mapping spoken language utterances to one of the natural language understanding domains in intelligent personal digital assistants (IPDAs). Thi…
Generalizing Word Embeddings using Bag of Subwords
Jinman Zhao, Sidharth Mudgal, Yingyu Liang
We approach the problem of generalizing pre-trained word embeddings beyond fixed-size vocabularies without using additional contextual information. We propose a subword-level word…