activity
20152025
most citedMultilingual Denoising Pre-training for Neural Machine Translation

607 citations · 1.1k across the 13 of their papers we have counts for

collaborators

19 papers

cs.CL202217 cited

In-context Examples Selection for Machine Translation

Sweta Agrawal, Chunting Zhou, Mike Lewis +2

Large-scale generative models show an impressive ability to perform a wide range of Natural Language Processing (NLP) tasks using in-context learning, where a few examples are used…

cs.CL202263 cited

A Review on Language Models as Knowledge Bases

Badr AlKhamissi, Millicent Li, Asli Celikyilmaz +2

Recently, there has been a surge of interest in the NLP community on the use of pretrained Language Models (LMs) as Knowledge Bases (KBs). Researchers have shown that LMs trained o…

cs.CL2021

Distributionally Robust Multilingual Machine Translation

Chunting Zhou, Daniel Levy, Xian Li +2

Multilingual neural machine translation (MNMT) learns to translate multiple language pairs with a single model, potentially improving both the accuracy and the memory-efficiency of…

cs.CL2021

Prompting Contrastive Explanations for Commonsense Reasoning Tasks

Bhargavi Paranjape, Julian Michael, Marjan Ghazvininejad +2

Many commonsense reasoning NLP tasks involve choosing between one or more possible answers to a question or prompt based on knowledge that is often implicit. Large pretrained langu…

cs.CL2021

EASE: Extractive-Abstractive Summarization with Explanations

Haoran Li, Arash Einolghozati, Srinivasan Iyer +4

Current abstractive summarization systems outperform their extractive counterparts, but their widespread adoption is inhibited by the inherent lack of interpretability. To achieve…

cs.CL20211 cited

Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog

Arun Babu, Akshat Shrivastava, Armen Aghajanyan +3

Semantic parsing using sequence-to-sequence models allows parsing of deeper representations compared to traditional word tagging based models. In spite of these advantages, widespr…