4 citations · 11 across the 8 of their papers we have counts for
8 papers
JECC: Commonsense Reasoning Tasks Derived from Interactive Fictions
Mo Yu, Yi Gu, Xiaoxiao Guo +5
Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an essential cornerstone in building general AI systems. We propose a new…
Neuro-symbolic Natural Logic with Introspective Revision for Natural Language Inference
Yufei Feng, Xiaoyu Yang, Xiaodan Zhu +1
We introduce a neuro-symbolic natural logic framework based on reinforcement learning with introspective revision. The model samples and rewards specific reasoning paths through po…
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…
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…
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…
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…
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…
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…