708 citations · 729 across the 5 of their papers we have counts for
6 papers
PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions
Anthony Chen, Panupong Pasupat, Sameer Singh +2
The remarkable capabilities of large language models have been accompanied by a persistent drawback: the generation of false and unsubstantiated claims commonly known as "hallucina…
RARR: Researching and Revising What Language Models Say, Using Language Models
Luyu Gao, Zhuyun Dai, Panupong Pasupat +8
Language models (LMs) now excel at many tasks such as few-shot learning, question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading conte…
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…
Generating Titles for Web Tables
Braden Hancock, Hongrae Lee, Cong Yu
Descriptive titles provide crucial context for interpreting tables that are extracted from web pages and are a key component of table-based web applications. Prior approaches have…
Learning to Skim Text
Adams Wei Yu, Hongrae Lee, Quoc V. Le
Recurrent Neural Networks are showing much promise in many sub-areas of natural language processing, ranging from document classification to machine translation to automatic questi…
Similarity Join Size Estimation using Locality Sensitive Hashing
Hongrae Lee, Raymond T. Ng, Kyuseok Shim
Similarity joins are important operations with a broad range of applications. In this paper, we study the problem of vector similarity join size estimation (VSJ). It is a generaliz…