Papers by Yichen Di

2 papers
WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large Documents (2025.findings-naacl)

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Challenge: Existing methods focus on distinguishing fully watermarked text from non-watermarked text, overlooking real-world scenarios where LLMs generate only brief segments within longer documents.
Approach: They propose a method to detect watermarked segments in large documents using an anomaly extraction method and a local traversal.
Outcome: The proposed method achieves a superior balance between detection accuracy and computational efficiency.
Robustness-Aware Word Embedding Improves Certified Robustness to Adversarial Word Substitutions (2023.findings-acl)

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Challenge: Embedding interval bound constraint is important for NLP models to be certified robust, but adversarial examples can be crafted by synonym substitutions.
Approach: They propose a triplet loss to train robustness-aware word embeddings for better certified robustness.
Outcome: The proposed method outperforms state-of-the-art certified defense baselines and generalizes well to unseen substitutions.

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