Papers by Yumeng Yang
Synergizing Stylometrics with Semantics: Dual-Path Framework for LLM Detection and Attribution (2026.findings-acl)
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| Challenge: | Existing methods for identifying MGTs rely on statistical likelihood or deep embeddings. |
| Approach: | They propose a framework that extracts model-specific stylistic fingerprints across lexical, syntactic, and structural dimensions. |
| Outcome: | The proposed framework achieves a Macro-F1 score of 95.6% on the Wikipedia dataset. |
CHENGYU-BENCH: Benchmarking Large Language Models for Chinese Idiom Understanding and Use (2025.emnlp-main)
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| Challenge: | Existing benchmarks focus on narrow tasks such as multiple-choice cloze tests, isolated translation, or simple paraphrasing. |
| Approach: | They propose a benchmark to measure Chinese idioms' cultural and contextual nuances . they evaluate 2,937 human-verified examples covering 1,765 common idiomes . |
| Outcome: | The proposed benchmarks achieve 95% accuracy on Evaluative Connotation, but only 85% on Appropriateness and 40% top-1 accuracy in Open Cloze. |
Unveiling the Generalization Power of Fine-Tuned Large Language Models (2024.naacl-long)
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| Challenge: | Large Language Models (LLMs) have demonstrated exceptional multitasking abilities, but the comprehensive effects of fine-tuning on the LLMs’ generalization ability are not fully understood. |
| Approach: | They conduct extensive experiments across five distinct language tasks on different datasets to investigate whether fine-tuning affects the generalization ability intrinsic to LLMs. |
| Outcome: | The proposed model can generalize to different domains and tasks by integrating the in-context learning strategy during fine-tuning on generation tasks. |
Stephanie: Step-by-Step Dialogues for Mimicking Human Interactions in Social Conversations (2025.findings-naacl)
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Hao Yang, Hongyuan Lu, Xinhua Zeng, Yang Liu, Xiang Zhang, Haoran Yang, Yumeng Zhang, Shan Huang, Yiran Wei, Wai Lam
| Challenge: | a new paradigm for dialogue systems is being developed to mimic human interactions . the current single-step dialogue paradigm lacks the depth and fluidity of human interactions. |
| Approach: | They propose a step-by-step dialogue paradigm that mimics human interactions . they use a dataset to fine-tune existing language models . |
| Outcome: | The proposed system mimics the dynamic nature of human conversations . it is compared with existing paradigms and will be released later this year . |
Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers across Diseases (2024.lrec-main)
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| Challenge: | Clinical trials are pivotal in medical research, and NLP can enhance their success with application in recruitment. |
| Approach: | They examine the generalizability of eligibility classification across clinical trials . they use an extensive cancer dataset to examine how well models can handle criteria . |
| Outcome: | The proposed model can handle criteria commonly found in non-cancer trials, but struggle with criteria disproportionately prevalent in cancer trials. |