4 citations · 16 across the 15 of their papers we have counts for
8 papers · 1 filter
FEANEL: A Benchmark for Fine-Grained Error Analysis in K-12 English Writing
Jingheng Ye, Shen Wang, Jiaqi Chen +9
Large Language Models (LLMs) have transformed artificial intelligence, offering profound opportunities for educational applications. However, their ability to provide fine-grained…
CLGEC: A Multi-Discipline Benchmark for Continual Learning in Chinese Literature Grammatical Error Correction
Shang Qin, Jingheng Ye, Yinghui Li +5
The growing demand for automated writing assistance in diverse academic domains highlights the need for robust Chinese Grammatical Error Correction (CGEC) systems that can adapt ac…
GMSA: Enhancing Context Compression via Group Merging and Layer Semantic Alignment
Jiwei Tang, Zhicheng Zhang, Shunlong Wu +8
Large Language Models (LLMs) have achieved remarkable performance across a wide range of Natural Language Processing (NLP) tasks. However, in long-context scenarios, they face two…
Corrections Meet Explanations: A Unified Framework for Explainable Grammatical Error Correction
Jingheng Ye, Shang Qin, Yinghui Li +3
Grammatical Error Correction (GEC) faces a critical challenge concerning explainability, notably when GEC systems are designed for language learners. Existing research predominantl…
Revisiting Classification Taxonomy for Grammatical Errors
Deqing Zou, Jingheng Ye, Yulu Liu +7
Grammatical error classification plays a crucial role in language learning systems, but existing classification taxonomies often lack rigorous validation, leading to inconsistencie…
EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models
Jiamin Su, Yibo Yan, Fangteng Fu +6
Automated Essay Scoring (AES) plays a crucial role in educational assessment by providing scalable and consistent evaluations of writing tasks. However, traditional AES systems fac…
Position: LLMs Can be Good Tutors in English Education
Jingheng Ye, Shen Wang, Deqing Zou +8
While recent efforts have begun integrating large language models (LLMs) into English education, they often rely on traditional approaches to learning tasks without fully embracing…
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning
Yibo Yan, Shen Wang, Jiahao Huo +7
Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, is essential in advancing knowled…