26 citations · 32 across the 10 of their papers we have counts for
10 papers
A Layered Taxonomy for Chinese Learner Grammatical Error Annotation
Mengyang Qiu, Jungyeul Park
Grammatical error annotation in Chinese learner writing requires labels that are both consistent and linguistically meaningful. This paper proposes a layered scheme linking computa…
Refining Word-Based Grammatical Error Annotation for L2 Korean
Jungyeul Park, Kyungtae Lim, Wonjun Oh +4
Korean grammatical error correction (K-GEC) presents a structural mismatch between word-based evaluation and the morpheme-level locus of many learner errors. Postpositions and verb…
A Formal Framework for Fluency-based Multi-Reference Evaluation in Grammatical Error Correction
Eitan Klinger, Zihao Huang, Tran Minh Nguyen +7
Evaluating grammatical error correction requires metrics that reflect the diversity of valid human corrections rather than privileging a single reference. Existing frameworks, larg…
Multilingual Grammatical Error Annotation: Combining Language-Agnostic Framework with Language-Specific Flexibility
Mengyang Qiu, Tran Minh Nguyen, Zihao Huang +5
Grammatical Error Correction (GEC) relies on accurate error annotation and evaluation, yet existing frameworks, such as , face limitations when extended to typolog…
Can LLMs Simulate Human Behavioral Variability? A Case Study in the Phonemic Fluency Task
Mengyang Qiu, Zoe Brisebois, Siena Sun
Large language models (LLMs) are increasingly explored as substitutes for human participants in cognitive tasks, but their ability to simulate human behavioral variability remains…
Chinese Grammatical Error Correction: A Survey
Mengyang Qiu, Qingyu Gao, Linxuan Yang +4
Chinese Grammatical Error Correction (CGEC) is a critical task in Natural Language Processing, addressing the growing demand for automated writing assistance in both second-languag…
Bias in Large Language Models: Origin, Evaluation, and Mitigation
Yufei Guo, Muzhe Guo, Juntao Su +5
Large Language Models (LLMs) have revolutionized natural language processing, but their susceptibility to biases poses significant challenges. This comprehensive review examines th…
Frustratingly Simple Prompting-based Text Denoising
Jungyeul Park, Mengyang Qiu
This paper introduces a novel perspective on the automated essay scoring (AES) task, challenging the conventional view of the ASAP dataset as a static entity. Employing simple text…
Evaluating Prompting Strategies for Grammatical Error Correction Based on Language Proficiency
Min Zeng, Jiexin Kuang, Mengyang Qiu +2
The writing examples of English language learners may be different from those of native speakers. Given that there is a significant differences in second language (L2) learners' er…
Neural Automated Writing Evaluation with Corrective Feedback
Izia Xiaoxiao Wang, Xihan Wu, Edith Coates +5
The utilization of technology in second language learning and teaching has become ubiquitous. For the assessment of writing specifically, automated writing evaluation (AWE) and gra…