Search Results for author: Jingxuan Tu

Found 5 papers, 0 papers with code

Designing Multimodal Datasets for NLP Challenges

no code implementations12 May 2021 James Pustejovsky, Eben Holderness, Jingxuan Tu, Parker Glenn, Kyeongmin Rim, Kelley Lynch, Richard Brutti

In this paper, we argue that the design and development of multimodal datasets for natural language processing (NLP) challenges should be enhanced in two significant respects: to more broadly represent commonsense semantic inferences; and to better reflect the dynamics of actions and events, through a substantive alignment of textual and visual information.

TMR: Evaluating NER Recall on Tough Mentions

no code implementations EACL 2021 Jingxuan Tu, Constantine Lignos

We propose the Tough Mentions Recall (TMR) metrics to supplement traditional named entity recognition (NER) evaluation by examining recall on specific subsets of "tough" mentions: unseen mentions, those whose tokens or token/type combination were not observed in training, and type-confusable mentions, token sequences with multiple entity types in the test data.

Named Entity Recognition NER

Exploration and Discovery of the COVID-19 Literature through Semantic Visualization

no code implementations NAACL 2021 Jingxuan Tu, Marc Verhagen, Brent Cochran, James Pustejovsky

We are developing semantic visualization techniques in order to enhance exploration and enable discovery over large datasets of complex networks of relations.

Knowledge Graphs TAG

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