activity
20172022
most citedLaMDA: Language Models for Dialog Applications

708 citations · 819 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL20226 cited

Transcending Scaling Laws with 0.1% Extra Compute

Yi Tay, Jason Wei, Hyung Won Chung +13

Scaling language models improves performance but comes with significant computational costs. This paper proposes UL2R, a method that substantially improves existing language models…

cs.CL2022708 cited

LaMDA: Language Models for Dialog Applications

Romal Thoppilan, Daniel De Freitas, Jamie Hall +57

We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of Transformer-based neural language models specialized for dialog, which have up to 137B parameters an…

cs.CL20202 cited

Joint Contextual Modeling for ASR Correction and Language Understanding

Yue Weng, Sai Sumanth Miryala, Chandra Khatri +8

The quality of automatic speech recognition (ASR) is critical to Dialogue Systems as ASR errors propagate to and directly impact downstream tasks such as language understanding (LU…

cs.CL2020

Exploration Based Language Learning for Text-Based Games

Andrea Madotto, Mahdi Namazifar, Joost Huizinga +7

This work presents an exploration and imitation-learning-based agent capable of state-of-the-art performance in playing text-based computer games. Text-based computer games describ…

cs.CL2019

Flexibly-Structured Model for Task-Oriented Dialogues

Lei Shu, Piero Molino, Mahdi Namazifar +4

This paper proposes a novel end-to-end architecture for task-oriented dialogue systems. It is based on a simple and practical yet very effective sequence-to-sequence approach, wher…

cs.CL201910 cited

OCC: A Smart Reply System for Efficient In-App Communications

Yue Weng, Huaixiu Zheng, Franziska Bell +1

Smart reply systems have been developed for various messaging platforms. In this paper, we introduce Uber's smart reply system: one-click-chat (OCC), which is a key enhanced featur…