153 citations · 303 across the 15 of their papers we have counts for
16 papers
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…
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning
Xiaoxiao Guo, Mo Yu, Yupeng Gao +3
Interactive Fiction (IF) games with real human-written natural language texts provide a new natural evaluation for language understanding techniques. In contrast to previous text g…
A Study of Compositional Generalization in Neural Models
Tim Klinger, Dhaval Adjodah, Vincent Marois +4
Compositional and relational learning is a hallmark of human intelligence, but one which presents challenges for neural models. One difficulty in the development of such models is…
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…
Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering
Wenhan Xiong, Mo Yu, Xiaoxiao Guo +4
A key challenge of multi-hop question answering (QA) in the open-domain setting is to accurately retrieve the supporting passages from a large corpus. Existing work on open-domain…
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy +5
Using machine learning in high-stakes applications often requires predictions to be accompanied by explanations comprehensible to the domain user, who has ultimate responsibility f…