5.7k citations · 8.7k across the 45 of their papers we have counts for
5 papers · 2 filters
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Nan Du, Yanping Huang, Andrew M. Dai +24
Scaling language models with more data, compute and parameters has driven significant progress in natural language processing. For example, thanks to scaling, GPT-3 was able to ach…
SGD-X: A Benchmark for Robust Generalization in Schema-Guided Dialogue Systems
Harrison Lee, Raghav Gupta, Abhinav Rastogi +3
Zero/few-shot transfer to unseen services is a critical challenge in task-oriented dialogue research. The Schema-Guided Dialogue (SGD) dataset introduced a paradigm for enabling mo…
Effective Sequence-to-Sequence Dialogue State Tracking
Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang +2
Sequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In…
PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS
Ye Jia, Heiga Zen, Jonathan Shen +2
This paper introduces PnG BERT, a new encoder model for neural TTS. This model is augmented from the original BERT model, by taking both phoneme and grapheme representations of tex…
Improving Longer-range Dialogue State Tracking
Ye Zhang, Yuan Cao, Mahdis Mahdieh +2
Dialogue state tracking (DST) is a pivotal component in task-oriented dialogue systems. While it is relatively easy for a DST model to capture belief states in short conversations,…