16 citations · 27 across the 9 of their papers we have counts for
6 papers · 1 filter
Leveraging Query Resolution and Reading Comprehension for Conversational Passage Retrieval
Svitlana Vakulenko, Nikos Voskarides, Zhucheng Tu +1
This paper describes the participation of UvA.ILPS group at the TREC CAsT 2020 track. Our passage retrieval pipeline consists of (i) an initial retrieval module that uses BM25, and…
A Comparison of Question Rewriting Methods for Conversational Passage Retrieval
Svitlana Vakulenko, Nikos Voskarides, Zhucheng Tu +1
Conversational passage retrieval relies on question rewriting to modify the original question so that it no longer depends on the conversation history. Several methods for question…
Open-Domain Question Answering Goes Conversational via Question Rewriting
Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu +3
We introduce a new dataset for Question Rewriting in Conversational Context (QReCC), which contains 14K conversations with 80K question-answer pairs. The task in QReCC is to find a…
Question Rewriting for Conversational Question Answering
Svitlana Vakulenko, Shayne Longpre, Zhucheng Tu +1
Conversational question answering (QA) requires the ability to correctly interpret a question in the context of previous conversation turns. We address the conversational QA task b…
An Exploration of Approaches to Integrating Neural Reranking Models in Multi-Stage Ranking Architectures
Zhucheng Tu, Matt Crane, Royal Sequiera +2
We explore different approaches to integrating a simple convolutional neural network (CNN) with the Lucene search engine in a multi-stage ranking architecture. Our models are train…
Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering
Royal Sequiera, Gaurav Baruah, Zhucheng Tu +4
Most work on natural language question answering today focuses on answer selection: given a candidate list of sentences, determine which contains the answer. Although important, an…