most citedTemporal Common Sense Acquisition with Minimal Supervision

12 citations · 15 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL202012 cited

Temporal Common Sense Acquisition with Minimal Supervision

Ben Zhou, Qiang Ning, Daniel Khashabi +1

Temporal common sense (e.g., duration and frequency of events) is crucial for understanding natural language. However, its acquisition is challenging, partly because such informati…

cs.CL2020

Cross-lingual Entity Alignment with Incidental Supervision

Muhao Chen, Weijia Shi, Ben Zhou +1

Much research effort has been put to multilingual knowledge graph (KG) embedding methods to address the entity alignment task, which seeks to match entities in different languagesp…

cs.CL2020

Evaluating Models' Local Decision Boundaries via Contrast Sets

Matt Gardner, Yoav Artzi, Victoria Basmova +23

Standard test sets for supervised learning evaluate in-distribution generalization. Unfortunately, when a dataset has systematic gaps (e.g., annotation artifacts), these evaluation…

cs.CL2019

"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding

Ben Zhou, Daniel Khashabi, Qiang Ning +1

Understanding time is crucial for understanding events expressed in natural language. Because people rarely say the obvious, it is often necessary to have commonsense knowledge abo…

cs.CL20192 cited

Zero-Shot Open Entity Typing as Type-Compatible Grounding

Ben Zhou, Daniel Khashabi, Chen-Tse Tsai +1

The problem of entity-typing has been studied predominantly in supervised learning fashion, mostly with task-specific annotations (for coarse types) and sometimes with distant supe…

cs.CL20191 cited

CogCompTime: A Tool for Understanding Time in Natural Language Text

Qiang Ning, Ben Zhou, Zhili Feng +2

Automatic extraction of temporal information in text is an important component of natural language understanding. It involves two basic tasks: (1) Understanding time expressions th…