Xilun Chen | DeepAI

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Jimmy Lin
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Sebastian Riedel
105 publications
Hannaneh Hajishirzi
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Xiaodong Liu
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Chitta Baral
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∙ 05/04/2023

VideoOFA: Two-Stage Pre-Training for Video-to-Text Generation

We propose a new two-stage pre-training framework for video-to-text gene...

0 Xilun Chen, et al. ∙

∙ 03/29/2023

Hierarchical Video-Moment Retrieval and Step-Captioning

There is growing interest in searching for information from large video ...

6 Abhay Zala, et al. ∙

∙ 02/15/2023

How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval

Various techniques have been developed in recent years to improve dense ...

0 Sheng-Chieh Lin, et al. ∙

∙ 12/02/2022

Nonparametric Masked Language Modeling

Existing language models (LMs) predict tokens with a softmax over a fini...

0 Sewon Min, et al. ∙

∙ 11/18/2022

CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval

Multi-vector retrieval methods combine the merits of sparse (e.g. BM25) ...

0 Minghan Li, et al. ∙

∙ 11/16/2022

Task-aware Retrieval with Instructions

We study the problem of retrieval with instructions, where users of a re...

0 Akari Asai, et al. ∙

∙ 10/04/2022

A Study on the Efficiency and Generalization of Light Hybrid Retrievers

Existing hybrid retrievers which integrate sparse and dense retrievers, ...

0 Man Luo, et al. ∙

∙ 12/14/2021

Simple Local Attentions Remain Competitive for Long-Context Tasks

Many NLP tasks require processing long contexts beyond the length limit ...

0 Wenhan Xiong, et al. ∙

∙ 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...

0 Patrick Huber, et al. ∙

∙ 10/13/2021

Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

Despite their recent popularity and well known advantages, dense retriev...

0 Xilun Chen, et al. ∙

∙ 07/28/2021

Domain-matched Pre-training Tasks for Dense Retrieval

Pre-training on larger datasets with ever increasing model size is now a...

0 Barlas Oguz, et al. ∙

∙ 01/26/2021

Muppet: Massive Multi-task Representations with Pre-Finetuning

We propose pre-finetuning, an additional large-scale learning stage betw...

4 Armen Aghajanyan, et al. ∙

∙ 01/01/2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...

15 Sewon Min, et al. ∙

∙ 12/29/2020

Unified Open-Domain Question Answering with Structured and Unstructured Knowledge

We study open-domain question answering (ODQA) with structured, unstruct...

0 Barlas Oguz, et al. ∙

∙ 10/07/2020

Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing

Task-oriented semantic parsing is a critical component of virtual assist...

0 Xilun Chen, et al. ∙

∙ 10/08/2018

Zero-Resource Multilingual Model Transfer: Learning What to Share

Modern natural language processing and understanding applications have e...

0 Xilun Chen, et al. ∙

∙ 08/27/2018

Unsupervised Multilingual Word Embeddings

Multilingual Word Embeddings (MWEs) represent words from multiple langua...

0 Xilun Chen, et al. ∙

∙ 02/15/2018

Multinomial Adversarial Networks for Multi-Domain Text Classification

Many text classification tasks are known to be highly domain-dependent. ...

0 Xilun Chen, et al. ∙

∙ 06/06/2016

Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification

In recent years deep neural networks have achieved great success in sent...

0 Xilun Chen, et al. ∙

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