7 papers
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…
How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers?
Shayne Longpre, Yu Wang, Christopher DuBois
Task-agnostic forms of data augmentation have proven widely effective in computer vision, even on pretrained models. In NLP similar results are reported most commonly for low data…
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…
On the Transferability of Minimal Prediction Preserving Inputs in Question Answering
Shayne Longpre, Yi Lu, Christopher DuBois
Recent work (Feng et al., 2018) establishes the presence of short, uninterpretable input fragments that yield high confidence and accuracy in neural models. We refer to these as Mi…
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…