Conversational Question Answering

35 papers with code • 0 benchmarks • 6 datasets

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Most implemented papers

CoQA: A Conversational Question Answering Challenge

stanfordnlp/coqa-baselines TACL 2019

Humans gather information by engaging in conversations involving a series of interconnected questions and answers.

SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering

Microsoft/SDNet 10 Dec 2018

Conversational question answering (CQA) is a novel QA task that requires understanding of dialogue context.

PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable

PaddlePaddle/Research ACL 2020

Pre-training models have been proved effective for a wide range of natural language processing tasks.

Attentive History Selection for Conversational Question Answering

prdwb/attentive_history_selection 26 Aug 2019

First, we propose a positional history answer embedding method to encode conversation history with position information using BERT in a natural way.

EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications

alibaba/EasyNLP 18 Nov 2020

The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP) applications, yet it is not easy to build an easy-to-use and scalable TL toolkit for this purpose.

Ditch the Gold Standard: Re-evaluating Conversational Question Answering

princeton-nlp/evalconvqa ACL 2022

In this work, we conduct the first large-scale human evaluation of state-of-the-art conversational QA systems, where human evaluators converse with models and judge the correctness of their answers.

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base

guoday/Dialog-to-Action NeurIPS 2018

We present an approach to map utterances in conversation to logical forms, which will be executed on a large-scale knowledge base.

BERT with History Answer Embedding for Conversational Question Answering

prdwb/bert_hae 14 May 2019

One of the major challenges to multi-turn conversational search is to model the conversation history to answer the current question.

An Empirical Study of Content Understanding in Conversational Question Answering

MiuLab/CQA-Study 24 Sep 2019

However, to best of our knowledge, two important questions for conversational comprehension research have not been well studied: 1) How well can the benchmark dataset reflect models' content understanding?