activity
20152019
most citedQuestion Answering and Question Generation as Dual Tasks

170 citations · 391 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV201926 cited

Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence

Peter Ström, Kimmo Kartasalo, Henrik Olsson +29

Background: An increasing volume of prostate biopsies and a world-wide shortage of uro-pathologists puts a strain on pathology departments. Additionally, the high intra- and inter-…

cs.CL201910 cited

Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing

Daya Guo, Duyu Tang, Nan Duan +2

In this paper, we present an approach to incorporate retrieved datapoints as supporting evidence for context-dependent semantic parsing, such as generating source code conditioned…

cs.CL201951 cited

HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization

Xingxing Zhang, Furu Wei, Ming Zhou

Neural extractive summarization models usually employ a hierarchical encoder for document encoding and they are trained using sentence-level labels, which are created heuristically…

cs.CL20183 cited

Assertion-based QA with Question-Aware Open Information Extraction

Zhao Yan, Duyu Tang, Nan Duan +5

We present assertion based question answering (ABQA), an open domain question answering task that takes a question and a passage as inputs, and outputs a semi-structured assertion…

cs.CL20176 cited

A Sequential Matching Framework for Multi-turn Response Selection in Retrieval-based Chatbots

Yu Wu, Wei Wu, Chen Xing +3

We study the problem of response selection for multi-turn conversation in retrieval-based chatbots. The task requires matching a response candidate with a conversation context, who…

cs.CL201747 cited

S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension

Chuanqi Tan, Furu Wei, Nan Yang +3

In this paper, we present a novel approach to machine reading comprehension for the MS-MARCO dataset. Unlike the SQuAD dataset that aims to answer a question with exact text spans…