most citedLearning to Retrieve Entity-Aware Knowledge and Generate Responses with Copy Mechanism for Task-Oriented Dialogue Systems

4 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL20212 cited

Complementary Evidence Identification in Open-Domain Question Answering

Xiangyang Mou, Mo Yu, Shiyu Chang +3

This paper proposes a new problem of complementary evidence identification for open-domain question answering (QA). The problem aims to efficiently find a small set of passages tha…

cs.CL20204 cited

Learning to Retrieve Entity-Aware Knowledge and Generate Responses with Copy Mechanism for Task-Oriented Dialogue Systems

Chao-Hong Tan, Xiaoyu Yang, Zi'ou Zheng +7

Task-oriented conversational modeling with unstructured knowledge access, as track 1 of the 9th Dialogue System Technology Challenges (DSTC 9), requests to build a system to genera…

cs.CL2020

Exploring End-to-End Differentiable Natural Logic Modeling

Yufei Feng, Zi'ou Zheng, Quan Liu +2

We explore end-to-end trained differentiable models that integrate natural logic with neural networks, aiming to keep the backbone of natural language reasoning based on the natura…

cs.AI2020

Deriving Commonsense Inference Tasks from Interactive Fictions

Mo Yu, Xiaoxiao Guo, Yufei Feng +3

Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems. We propose a…

cs.AI2020

Program Enhanced Fact Verification with Verbalization and Graph Attention Network

Xiaoyu Yang, Feng Nie, Yufei Feng +3

Performing fact verification based on structured data is important for many real-life applications and is a challenging research problem, particularly when it involves both symboli…

cs.CL20202 cited

Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games

Yufei Feng, Mo Yu, Wenhan Xiong +6

We propose the new problem of learning to recover reasoning chains from weakly supervised signals, i.e., the question-answer pairs. We propose a cooperative game approach to deal w…