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  • Influence
A Multi-Axis Annotation Scheme for Event Temporal Relations
TLDR
This paper proposes a new multi-axis modeling to better capture the temporal structure of events. Expand
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A Structured Learning Approach to Temporal Relation Extraction
TLDR
In this paper, we propose a structured learning approach to temporal relation extraction, where local models are updated based on feedback from global inferences. Expand
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Joint Reasoning for Temporal and Causal Relations
TLDR
Understanding temporal and causal relations between events is a fundamental natural language understanding task. Expand
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"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding
TLDR
We define five classes of temporal commonsense, and use crowdsourcing to develop a new dataset, MCTACO, that serves as a test set for this task. Expand
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Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource
TLDR
This paper develops such a resource -- a probabilistic knowledge base acquired in the news domain -- by extracting temporal relations between events from the New York Times (NYT) articles. Expand
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Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction
TLDR
We propose a joint event and temporal relation extraction model with shared representation learning and structured prediction. Expand
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CogCompTime: A Tool for Understanding Time in Natural Language
TLDR
We present CogCompTime, a system that has these two important functionalities. Expand
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High‐resolution 1H‐MRSI of the brain using short‐TE SPICE
TLDR
To improve signal‐to‐noise ratio (SNR) for high‐resolution spectroscopic imaging using a subspace‐based technique known as SPectroscopic Imaging by exploiting spatiospectral CorrElation (SPICE). Expand
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Tensor Decomposition
  • Qiang Ning
  • Computer Science
  • Encyclopedia of Social Network Analysis and…
  • 2018
TLDR
We introduce tensor decomposition as a generalization of matrix decomposition and also its unique properties that make it different to matrices. Expand
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Evaluating NLP Models via Contrast Sets
TLDR
We propose a new annotation paradigm for NLP that helps to close systematic gaps in the test data. Expand
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