Haneul Yoo

Orcid: 0000-0001-8266-6962

According to our database1, Haneul Yoo authored at least 15 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
KoBBQ: Korean Bias Benchmark for Question Answering.
Trans. Assoc. Comput. Linguistics, 2024

MAQA: Evaluating Uncertainty Quantification in LLMs Regarding Data Uncertainty.
CoRR, 2024

CHOP: Integrating ChatGPT into EFL Oral Presentation Practice.
CoRR, 2024

CSRT: Evaluation and Analysis of LLMs using Code-Switching Red-Teaming Dataset.
CoRR, 2024

Designing Prompt Analytics Dashboards to Analyze Student-ChatGPT Interactions in EFL Writing.
CoRR, 2024

DREsS: Dataset for Rubric-based Essay Scoring on EFL Writing.
CoRR, 2024

CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence in Korean.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

RECIPE4U: Student-ChatGPT Interaction Dataset in EFL Writing Education.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
FABRIC: Automated Scoring and Feedback Generation for Essays.
CoRR, 2023

RECIPE: How to Integrate ChatGPT into EFL Writing Education.
Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

Rethinking Annotation: Can Language Learners Contribute?
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Translating Hanja historical documents to understandable Korean and English.
CoRR, 2022

HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Translating Hanja Historical Documents to Contemporary Korean and English.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
Knowledge-Enhanced Evidence Retrieval for Counterargument Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021


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