Papers by Jiuming Wang

2 papers
Developing and Utilizing a Large-Scale Cantonese Dataset for Multi-Tasking in Large Language Models (2025.findings-emnlp)

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Challenge: Cantonese is considered a low-resource language due to the dominance of Mandarin . rich colloquial vocabulary of Cantone, English loanwords, and code-switching characteristics add to the complexity of corpus collection and processing.
Approach: We collect Cantonese texts from open source corpora, Hong Kong-specific forums, Wikipedia . we refine the model through supervised fine-tuning on curated Cantonesian tasks .
Outcome: The model achieves state-of-the-art (SOTA) performance on four Cantonese benchmarks.
RBPtool: A Deep Language Model Framework for Multi-Resolution RBP-RNA Binding Prediction and RNA Molecule Design (2025.emnlp-main)

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Challenge: RNA-binding proteins play key roles in post-transcriptional gene regulation . existing methods focus on shallow sequence features or coarse structural representations . large language models allow for precise modeling and biologically informed de novo RNA design .
Approach: They extend RPI15223 into a multi-resolution, structure-level RBP-RNA dataset and introduce RBPtool, a framework that fuses sequence and structural information.
Outcome: The proposed framework achieves state-of-the-art performance on public benchmarks and the RPI15223 dataset while supporting fine-grained level predictions.

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