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05/23/2023
DUBLIN – Document Understanding By Language-Image Network
Visual document understanding is a complex task that involves analyzing ...
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04/13/2022
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals
We present an efficient method of pretraining large-scale autoencoding l...
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04/07/2022
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
We present a new framework AMOS that pretrains text encoders with an Adv...
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01/28/2022
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model
Pretrained general-purpose language models can achieve state-of-the-art ...
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02/16/2021
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
We present COCO-LM, a new self-supervised learning framework that pretra...
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06/29/2020
Knowledge-Aware Language Model Pretraining
How much knowledge do pretrained language models hold? Recent research o...
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07/24/2019
Generic Intent Representation in Web Search
This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a ...
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04/15/2019
An Axiomatic Approach to Regularizing Neural Ranking Models
Axiomatic information retrieval (IR) seeks a set of principle properties...
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09/23/2018
Towards Language Agnostic Universal Representations
When a bilingual student learns to solve word problems in math, we expec...
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04/12/2018
Optimizing Query Evaluations using Reinforcement Learning for Web Search
In web search, typically a candidate generation step selects a small set...
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11/25/2017
Neural Ranking Models with Multiple Document Fields
Deep neural networks have recently shown promise in the ad-hoc retrieval...
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11/28/2016