Papers by Sufeng Duan

3 papers
Encoder and Decoder, Not One Less for Pre-trained Language Model Sponsored NMT (2023.findings-acl)

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Challenge: Existing methods for neural machine translation (NMT) use encoder-only enhancement or rely on specific multilingual PLMs.
Approach: They propose a monolingual PLM-sponsored NMT model that lets both encoder and decoder enjoy PLM enhancement.
Outcome: The proposed model improves on IWSLT14 En-De, De-En, WMT14 En -De and En-Fr tasks and achieves new state-of-the-art.
Attention Is All You Need for Chinese Word Segmentation (2020.emnlp-main)

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Challenge: Recent work on Chinese word segmentation has been concerned about the following three perspectives.
Approach: They propose to use a greedy decoding algorithm to improve Chinese word segmentation model.
Outcome: The proposed model achieves state-of-the-art or comparable performance against strong baselines in strict closed test setting.
ALIS: Aligned LLM Instruction Security Strategy for Unsafe Input Prompt (2025.coling-main)

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Challenge: Existing instruction tuning methods may fail to balance performance with robustness against attacks from user input like prompt injection and jailbreaking.
Approach: They propose an instruction tuning paradigm to decompose user inputs into irreducible atomic instructions and organize them into instruction streams to guide response generation of model.
Outcome: The proposed model can maintain security constraints by ignoring or rejecting user mode instructions when user mode instruction conflicts with kernel mode instructions.

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