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02/07/2023
Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories
In this paper we improve the zero-shot generalization ability of languag...
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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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01/13/2022
Neural Approaches to Conversational Information Retrieval
A conversational information retrieval (CIR) system is an information re...
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07/07/2021
Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text
This work presents Keep it Simple (KiS), a new approach to unsupervised ...
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02/18/2021
Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder
Many real-world applications use Siamese networks to efficiently match t...
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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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12/29/2020
Meta Adaptive Neural Ranking with Contrastive Synthetic Supervision
Neural Information Retrieval (Neu-IR) models have shown their effectiven...
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11/03/2020
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search
Neural rankers based on deep pretrained language models (LMs) have been ...
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07/01/2020
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Conducting text retrieval in a dense learned representation space has ma...
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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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06/09/2020