Search Results for author: Zhucheng Tu

Found 11 papers, 4 papers with code

A Comparison of Question Rewriting Methods for Conversational Passage Retrieval

1 code implementation19 Jan 2021 Svitlana Vakulenko, Nikos Voskarides, Zhucheng Tu, Shayne Longpre

Conversational passage retrieval relies on question rewriting to modify the original question so that it no longer depends on the conversation history.

Passage Retrieval Question Rewriting +1

Question Rewriting for Conversational Question Answering

no code implementations30 Apr 2020 Svitlana Vakulenko, Shayne Longpre, Zhucheng Tu, Raviteja Anantha

Conversational question answering (QA) requires the ability to correctly interpret a question in the context of previous conversation turns.

Passage Retrieval Question Rewriting +1

Least squares binary quantization of neural networks

1 code implementation9 Jan 2020 Hadi Pouransari, Zhucheng Tu, Oncel Tuzel

We conduct experiments on the ImageNet dataset and show a reduced accuracy gap when using the proposed least squares quantization algorithms.


An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering

no code implementations WS 2019 Shayne Longpre, Yi Lu, Zhucheng Tu, Chris DuBois

To produce a domain-agnostic question answering model for the Machine Reading Question Answering (MRQA) 2019 Shared Task, we investigate the relative benefits of large pre-trained language models, various data sampling strategies, as well as query and context paraphrases generated by back-translation.

Data Augmentation Question Answering +2

Pay-Per-Request Deployment of Neural Network Models Using Serverless Architectures

no code implementations NAACL 2018 Zhucheng Tu, Mengping Li, Jimmy Lin

We demonstrate the serverless deployment of neural networks for model inferencing in NLP applications using Amazon{'}s Lambda service for feedforward evaluation and DynamoDB for storing word embeddings.

Answer Selection Management +2

Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering

no code implementations25 Jul 2017 Royal Sequiera, Gaurav Baruah, Zhucheng Tu, Salman Mohammed, Jinfeng Rao, Haotian Zhang, Jimmy Lin

Most work on natural language question answering today focuses on answer selection: given a candidate list of sentences, determine which contains the answer.

Answer Selection Retrieval

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