Papers by Qianqian Zhuang

2 papers
InteGround: On the Evaluation of Verification and Retrieval Planning in Integrative Grounding (2025.findings-emnlp)

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Challenge: Existing grounding approaches work well for simple queries, but many real-world information needs require synthesizing multiple pieces of evidence.
Approach: They introduce "integrative grounding" to evaluate the ability to ground large language models in external knowledge sources.
Outcome: The proposed approach is robust to redundant evidence, but rationalizes using internal knowledge when information is incomplete.
ECON: On the Detection and Resolution of Evidence Conflicts (2024.emnlp-main)

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Challenge: Recent studies have shown that AI generated content is more likely to dominate search results, making it difficult to detect when compared to human-produced content.
Approach: They propose a method for generating diverse, validated evidence conflicts to simulate real-world misinformation scenarios.
Outcome: The proposed method enables the detection of conflicting information in real-world scenarios and shows that weaker models struggle with similar answer conflicts while stronger models show robust performance.

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