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Ting-Hao 'Kenneth' Huang

Are Shortest Rationales the Best Explanations for Human Understanding?



Hua Shen , Tongshuang Wu , Wenbo Guo , Ting-Hao 'Kenneth' Huang

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* To appear in ACL 2022 main conference 
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SciCap: Generating Captions for Scientific Figures



Ting-Yao Hsu , C. Lee Giles , Ting-Hao 'Kenneth' Huang

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* To Appear in EMNLP 2021 Findings. The dataset is available at: https://github.com/tingyaohsu/SciCap 
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Empowering Local Communities Using Artificial Intelligence



Yen-Chia Hsu , Ting-Hao 'Kenneth' Huang , Himanshu Verma , Andrea Mauri , Illah Nourbakhsh , Alessandro Bozzon

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* this manuscript was submitted to a journal and is currently under review 
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Plot and Rework: Modeling Storylines for Visual Storytelling



Chi-Yang Hsu , Yun-Wei Chu , Ting-Hao 'Kenneth' Huang , Lun-Wei Ku

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* Accepted by ACL'21 Findings; this is not the camera-ready version 
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Semantic Frame Forecast



Chieh-Yang Huang , Ting-Hao 'Kenneth' Huang

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* 9 pages, NAACL 2021 
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Explaining the Road Not Taken



Hua Shen , Ting-Hao 'Kenneth' Huang

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* Accepted by The 2021 ACM CHI Workshop on Operationalizing Human-Centered Perspectives in Explainable AI (CHI 2021 HCXAI Workshop). For associated website, see https://human-centered-exnlp.github.io 
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Assessing the Helpfulness of Learning Materials with Inference-Based Learner-Like Agent



Yun-Hsuan Jen , Chieh-Yang Huang , Mei-Hua Chen , Ting-Hao 'Kenneth' Huang , Lun-Wei Ku

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* 9 pages, to appear in EMNLP 2020 as a long paper 
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How Useful Are the Machine-Generated Interpretations to General Users? A Human Evaluation on Guessing the Incorrectly Predicted Labels



Hua Shen , Ting-Hao 'Kenneth' Huang

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* Accepted by The 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2020) https://github.com/huashen218/GuessWrongLabel 
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RISE Video Dataset: Recognizing Industrial Smoke Emissions



Yen-Chia Hsu , Ting-Hao 'Kenneth' Huang , Ting-Yao Hu , Paul Dille , Sean Prendi , Ryan Hoffman , Anastasia Tsuhlares , Randy Sargent , Illah Nourbakhsh

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* Technical report 
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CODA-19: Reliably Annotating Research Aspects on 10,000+ CORD-19 Abstracts Using a Non-Expert Crowd



Ting-Hao 'Kenneth' Huang , Chieh-Yang Huang , Chien-Kuang Cornelia Ding , Yen-Chia Hsu , C. Lee Giles

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* CODA-19: COVID-19 Research Aspect Dataset: https://github.com/windx0303/CODA-19 
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