406 citations · 2.4k across the 39 of their papers we have counts for
6 papers · 1 filter
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +12
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…
Automatic Document Sketching: Generating Drafts from Analogous Texts
Zeqiu Wu, Michel Galley, Chris Brockett +2
The advent of large pre-trained language models has made it possible to make high-quality predictions on how to add or change a sentence in a document. However, the high branching…
RetGen: A Joint framework for Retrieval and Grounded Text Generation Modeling
Yizhe Zhang, Siqi Sun, Xiang Gao +5
Recent advances in large-scale pre-training such as GPT-3 allow seemingly high quality text to be generated from a given prompt. However, such generation systems often suffer from…
An Adversarially-Learned Turing Test for Dialog Generation Models
Xiang Gao, Yizhe Zhang, Michel Galley +1
The design of better automated dialogue evaluation metrics offers the potential of accelerate evaluation research on conversational AI. However, existing trainable dialogue evaluat…
Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge
Bodhisattwa Prasad Majumder, Sudha Rao, Michel Galley +1
The ability to generate clarification questions i.e., questions that identify useful missing information in a given context, is important in reducing ambiguity. Humans use previous…
Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley +4
The progress in Query-focused Multi-Document Summarization (QMDS) has been limited by the lack of sufficient largescale high-quality training datasets. We present two QMDS training…