607 citations · 1.1k across the 7 of their papers we have counts for
14 papers
Conversational Semantic Parsing
Armen Aghajanyan, Jean Maillard, Akshat Shrivastava +8
The structured representation for semantic parsing in task-oriented assistant systems is geared towards simple understanding of one-turn queries. Due to the limitations of the repr…
Pre-training via Paraphrasing
Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh +3
We introduce MARGE, a pre-trained sequence-to-sequence model learned with an unsupervised multi-lingual multi-document paraphrasing objective. MARGE provides an alternative to the…
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
Alex Wang, Kyunghyun Cho, Mike Lewis
Practical applications of abstractive summarization models are limited by frequent factual inconsistencies with respect to their input. Existing automatic evaluation metrics for su…
Multilingual Denoising Pre-training for Neural Machine Translation
Yinhan Liu, Jiatao Gu, Naman Goyal +5
This paper demonstrates that multilingual denoising pre-training produces significant performance gains across a wide variety of machine translation (MT) tasks. We present mBART --…
Enforcing Encoder-Decoder Modularity in Sequence-to-Sequence Models
Siddharth Dalmia, Abdelrahman Mohamed, Mike Lewis +2
Inspired by modular software design principles of independence, interchangeability, and clarity of interface, we introduce a method for enforcing encoder-decoder modularity in seq2…
Generalization through Memorization: Nearest Neighbor Language Models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky +2
We introduce NN-LMs, which extend a pre-trained neural language model (LM) by linearly interpolating it with a -nearest neighbors (NN) model. The nearest neighbors are com…