activity
20162023
most citedRetrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

3.1k citations · 5.5k across the 54 of their papers we have counts for

collaborators
Showing 2019Show all

8 papers · 1 filter

cs.CL2019★ 11 cited

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…

cs.CL2019★ 55 cited

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…

cs.CL2019★ 241 cited

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Mike Lewis, Yinhan Liu, Naman Goyal +5

We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. BART is trained by (1) corrupting text with an arbitrary noising function, and (2) learning a…

cs.CL2019

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Yinhan Liu, Myle Ott, Naman Goyal +7

Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging. Training is computationally expensive, often…

eess.AS2019★ 112 cited

MelNet: A Generative Model for Audio in the Frequency Domain

Sean Vasquez, Mike Lewis

Capturing high-level structure in audio waveforms is challenging because a single second of audio spans tens of thousands of timesteps. While long-range dependencies are difficult…

cs.AI2019★ 33 cited

Hierarchical Decision Making by Generating and Following Natural Language Instructions

Hengyuan Hu, Denis Yarats, Qucheng Gong +2

We explore using latent natural language instructions as an expressive and compositional representation of complex actions for hierarchical decision making. Rather than directly se…

cs.CL2019★ 25 cited

Improving Semantic Parsing for Task Oriented Dialog

Arash Einolghozati, Panupong Pasupat, Sonal Gupta +4

Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018]. In this paper, we present three d…

cs.CL2019★ 17 cited

Strategies for Structuring Story Generation

Angela Fan, Mike Lewis, Yann Dauphin

Writers generally rely on plans or sketches to write long stories, but most current language models generate word by word from left to right. We explore coarse-to-fine models for c…