30 citations · 71 across the 16 of their papers we have counts for
17 papers
If in a Crowdsourced Data Annotation Pipeline, a GPT-4
Zeyu He, Chieh-Yang Huang, Chien-Kuang Cornelia Ding +2
Recent studies indicated GPT-4 outperforms online crowd workers in data labeling accuracy, notably workers from Amazon Mechanical Turk (MTurk). However, these studies were criticiz…
Inspo: Writing with Crowds Alongside AI
Chieh-Yang Huang, Sanjana Gautam, Shannon McClellan Brooks +3
The use of artificial intelligence (AI) to support creative writing has bloomed in recent years. However, it is less well understood how AI compares to on-demand human support. We…
Good Data, Large Data, or No Data? Comparing Three Approaches in Developing Research Aspect Classifiers for Biomedical Papers
Shreya Chandrasekhar, Chieh-Yang Huang, Ting-Hao 'Kenneth' Huang
The rapid growth of scientific publications, particularly during the COVID-19 pandemic, emphasizes the need for tools to help researchers efficiently comprehend the latest advancem…
ConvXAI: Delivering Heterogeneous AI Explanations via Conversations to Support Human-AI Scientific Writing
Hua Shen, Chieh-Yang Huang, Tongshuang Wu +1
Despite a surge collection of XAI methods, users still struggle to obtain required AI explanations. Previous research suggests chatbots as dynamic solutions, but the effective desi…
What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questions
Shih-Hong Huang, Chieh-Yang Huang, Ya-Fang Lin +1
The proliferation of automated conversational systems such as chatbots, spoken-dialogue systems, and smart speakers, has significantly impacted modern digital life. However, these…
Conveying the Predicted Future to Users: A Case Study of Story Plot Prediction
Chieh-Yang Huang, Saniya Naphade, Kavya Laalasa Karanam +1
Creative writing is hard: Novelists struggle with writer's block daily. While automatic story generation has advanced recently, it is treated as a "toy task" for advancing artifici…
Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization
Chieh-Yang Huang, Ting-Yao Hsu, Ryan Rossi +6
Good figure captions help paper readers understand complex scientific figures. Unfortunately, even published papers often have poorly written captions. Automatic caption generation…
Too Slow to Be Useful? On Incorporating Humans in the Loop of Smart Speakers
Shih-Hong Huang, Chieh-Yang Huang, Yuxin Deng +3
Real-time crowd-powered systems, such as Chorus/Evorus, VizWiz, and Apparition, have shown how incorporating humans into automated systems could supplement where the automatic solu…
Semantic Frame Forecast
Chieh-Yang Huang, Ting-Hao 'Kenneth' Huang
This paper introduces semantic frame forecast, a task that predicts the semantic frames that will occur in the next 10, 100, or even 1,000 sentences in a running story. Prior work…
Assessing the Helpfulness of Learning Materials with Inference-Based Learner-Like Agent
Yun-Hsuan Jen, Chieh-Yang Huang, Mei-Hua Chen +2
Many English-as-a-second language learners have trouble using near-synonym words (e.g., small vs.little; briefly vs.shortly) correctly, and often look for example sentences to lear…
TEST_POSITIVE at W-NUT 2020 Shared Task-3: Joint Event Multi-task Learning for Slot Filling in Noisy Text
Chacha Chen, Chieh-Yang Huang, Yaqi Hou +3
The competition of extracting COVID-19 events from Twitter is to develop systems that can automatically extract related events from tweets. The built system should identify differe…
CODA-19: Using a Non-Expert Crowd to Annotate Research Aspects on 10,000+ Abstracts in the COVID-19 Open Research Dataset
Ting-Hao 'Kenneth' Huang, Chieh-Yang Huang, Chien-Kuang Cornelia Ding +2
This paper introduces CODA-19, a human-annotated dataset that codes the Background, Purpose, Method, Finding/Contribution, and Other sections of 10,966 English abstracts in the COV…
Heteroglossia: In-Situ Story Ideation with the Crowd
Chieh-Yang Huang, Shih-Hong Huang, Ting-Hao 'Kenneth' Huang
Ideation is essential for creative writing. Many authors struggle to come up with ideas throughout the writing process, yet modern writing tools fail to provide on-the-spot assista…
From Receptive to Productive: Learning to Use Confusing Words through Automatically Selected Example Sentences
Chieh-Yang Huang, Yi-Ting Huang, Mei-Hua Chen +1
Knowing how to use words appropriately has been a key to improving language proficiency. Previous studies typically discuss how students learn receptively to select the correct can…
Visual Story Post-Editing
Ting-Yao Hsu, Chieh-Yang Huang, Yen-Chia Hsu +1
We introduce the first dataset for human edits of machine-generated visual stories and explore how these collected edits may be used for the visual story post-editing task. The dat…
MoodSwipe: A Soft Keyboard that Suggests Messages Based on User-Specified Emotions
Chieh-Yang Huang, Tristan Labetoulle, Ting-Hao Kenneth Huang +4
We present MoodSwipe, a soft keyboard that suggests text messages given the user-specified emotions utilizing the real dialog data. The aim of MoodSwipe is to create a convenient u…
Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications
Chieh-Yang Huang, Ting-Hao, Huang +1
Instant messaging is one of the major channels of computer mediated communication. However, humans are known to be very limited in understanding others' emotions via text-based com…