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06/07/2022
LegoNN: Building Modular Encoder-Decoder Models
State-of-the-art encoder-decoder models (e.g. for machine translation (M...
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01/19/2022
CM3: A Causal Masked Multimodal Model of the Internet
We introduce CM3, a family of causally masked generative models trained ...
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12/18/2021
The Web Is Your Oyster – Knowledge-Intensive NLP against a Very Large Web Corpus
In order to address the increasing demands of real-world applications, t...
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10/14/2021
CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training
With the rise of large-scale pre-trained language models, open-domain qu...
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09/28/2021
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding
We present VideoCLIP, a contrastive approach to pre-train a unified mode...
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07/14/2021
HTLM: Hyper-Text Pre-Training and Prompting of Language Models
We introduce HTLM, a hyper-text language model trained on a large-scale ...
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01/01/2021
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020. The competition...
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12/29/2020
Unified Open-Domain Question Answering with Structured and Unstructured Knowledge
We study open-domain question answering (ODQA) with structured, unstruct...
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10/11/2020
fairseq S2T: Fast Speech-to-Text Modeling with fairseq
We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) m...
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10/27/2019
Training ASR models by Generation of Contextual Information
Supervised ASR models have reached unprecedented levels of accuracy, tha...
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04/26/2019
