Mengyang Qiu

Mengyang Qiu

About

16
Publications
1,243
Reads
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45
Citations
Education
August 2018 - June 2019
University at Buffalo, State University of New York
Field of study
  • Computational Linguistics
August 2016 - February 2024
University at Buffalo, State University of New York
Field of study
  • Communicative Disorders and Sciences (CogSci Track)
August 2013 - February 2016

Publications

Publications (16)
Preprint
Full-text available
Chinese Grammatical Error Correction (CGEC) is a critical task in Natural Language Processing, addressing the growing demand for automated writing assistance in both second-language (L2) and native (L1) Chinese writing. While L2 learners struggle with mastering complex grammatical structures, L1 users also benefit from CGEC in academic, professiona...
Preprint
The lexemes ‘fruit’ and ‘stone’ are known as the origins of the numeral classifiers for small round objects in many Tibeto-Burman languages. This paper employs a correlation-based network construction method to investigate the colexification networks of the two concepts in 58 + 68 Tibeto-Burman languages. A total of 104 concepts colexified with ‘fr...
Conference Paper
Full-text available
We propose a refined alignment-based method to assess end-to-end grammatical error correction (GEC) systems, aiming to reproduce and improve results from existing evaluation tools, such as errant, even when applied to raw text input-reflecting real-world language learners' writing scenarios. Our approach addresses challenges arising from sentence b...
Conference Paper
Full-text available
Comprehensive error annotation is essential for developing effective Grammatical Error Correction (GEC) systems and delivering meaningful feedback to learners. This paper introduces improvements to automatic grammatical error annotation for Chinese. Our refined framework addresses language-specific challenges that cause common spelling errors in Ch...
Preprint
Full-text available
Large Language Models (LLMs) have revolutionized natural language processing, but their susceptibility to biases poses significant challenges. This comprehensive review examines the landscape of bias in LLMs, from its origins to current mitigation strategies. We categorize biases as intrinsic and extrinsic, analyzing their manifestations in various...
Article
Full-text available
Purpose The purpose of the current study was to estimate the minimal clinically important difference (MCID) of sentence intelligibility in control speakers and in speakers with dysarthria due to multiple sclerosis (MS) and Parkinson's disease (PD). Method Sixteen control speakers, 16 speakers with MS, and 16 speakers with PD were audio-recorded re...
Conference Paper
Full-text available
This study introduces a novel approach for quantifying individual differences in print exposure through the integration of dis-tributional semantics with the Author Production Test (APT). By employing the Universal Sentence Encoder to generate vector representations of authors from their works, we constructed 'participant vectors' reflecting the ag...
Conference Paper
Full-text available
This paper proposes an analysis of prompting strategies for grammatical error correction (GEC) with selected large language models (LLM) based on language proficiency. GEC using generative LLMs has been known for overcorrection where results obtain higher recall measures than precision measures. The writing examples of English language learners may...
Conference Paper
Full-text available
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 denoising techniques using prompting, we explore the dynamic potential within the dataset. While acknowledging the previous emphasis on building regression systems, our...
Preprint
Full-text available
The utilization of technology in second language learning and teaching has become ubiquitous. For the assessment of writing specifically, automated writing evaluation (AWE) and grammatical error correction (GEC) have become immensely popular and effective methods for enhancing writing proficiency and delivering instant and individualized feedback t...
Thesis
Full-text available
This dissertation investigates the information accumulation perspective of cognitive aging, which posits that differences in accumulated knowledge, rather than declines in cognitive abilities, may account for age-related variances in linguistic and cognitive task performance. Through four studies, it provides evidence for this perspective and propo...
Preprint
Full-text available
The lexemes ‘fruit’ and ‘stone’ are known as the origins of the numeral classifiers for small round objects in many Tibeto-Burman languages. This paper employs a correlation-based network construction method to investigate the colexification networks of the two concepts in 60 + 68 Tibeto-Burman languages. A total of 104 concepts colexified with ‘fr...
Conference Paper
Full-text available
Recent studies have applied network-based approaches to analyze the organization and retrieval of specific semantic categories , with a focus on the animal category. The current study extended previous studies by using network science tools to quantitatively investigate the structural differences of noun and verb categories of various levels of spe...
Preprint
Category verbal fluency tasks, where participants are asked to produce words according to a semantic category, are typically noun-based (e.g., animals). While insights about the integrity and retrieval of semantic knowledge have been obtained by analyzing the ordinal variances of word production in these noun-based fluency tasks, focusing exclusive...
Article
Full-text available
Normal aging is often associated with a performance decline on various cognitive tests, including paired associate learning (PAL), where participants are asked to learn and recall arbitrary word pairs. While many studies have taken this as evidence to support the notion of age-related deficits in cognitive processing, Ramscar, Hendrix, Shaoul, Mili...

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