Papers by Xiaobo Shen

2 papers
PoemBERT: A Dynamic Masking Content and Ratio Based Semantic Language Model For Chinese Poem Generation (2025.coling-main)

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Challenge: Despite the lack of pre-trained models for ancient Chinese poetry, the unique artistry and structural nuances of Chinese poetry present complex challenges for machine learning in creative applications.
Approach: They propose a BERT-based model incorporating sentiment and pinyin embeddings into the model, enhancing its sensitivity to emotional information and addressing challenges posed by the phenomenon of multiple pronunciations for the same Chinese character.
Outcome: The proposed model outperforms existing models on poem generation and sentiment classification tasks and is state-of-the-art in automatic and manual evaluations.
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct (2025.findings-acl)

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Challenge: a new framework for image-text instruction data evolution improves MLLM performance . lack of high-quality instruction data remains a major bottleneck in ML modeling .
Approach: They propose a multimodal instruction data evolution framework that iteratively enhances data quality through fine-grained perception, cognitive reasoning, and interaction evolution.
Outcome: The proposed approach improves MLLM performance in nine vision-language tasks while using significantly less data.

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