Papers by Zhixiong Su

2 papers
On the Risk of Evidence Pollution for Malicious Social Text Detection in the Era of LLMs (2025.acl-long)

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Challenge: Evidence-enhanced detectors are able to detect malicious social text, but they are prone to evidence pollution.
Approach: They propose three defense strategies to mitigate evidence pollution by large language models by machine-generated text detection and a mixture of experts.
Outcome: The proposed defense strategies could mitigate evidence pollution, but they faced limitations for practical employment.
HACo-Det: A Study Towards Fine-Grained Machine-Generated Text Detection under Human-AI Coauthoring (2025.acl-long)

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Challenge: Existing literature focuses on binary, document-level detection, neglecting texts composed jointly by human and LLM contributions.
Approach: They propose to use a dataset to generate human-AI coauthored texts via an automatic pipeline with word-level attribution labels.
Outcome: The proposed method can detect human-AI coauthored texts with a numeric AI ratio.

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