Papers by Haokai Hong

2 papers
PII-Bench: Evaluating Query-Aware Privacy Protection Systems (2026.acl-long)

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Challenge: Existing models do not detect PII in user prompts, despite their convenience . current models show significant limitations in determining PI I query relevance .
Approach: They propose a query-unrelated PII masking strategy and propose PIi-Bench . they propose 'quick-and-easy' PI I masking with a user query and context description .
Outcome: The proposed model performs well in basic PII detection, but shows significant limitations in query relevance.
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems (2025.acl-industry)

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Challenge: Large Language Models (LLMs) can be used to broaden user experiences beyond established preferences and reinforce feedback loops.
Approach: They propose a hierarchical approach that combines hierarchic planning with LLM inference-time scaling to improve recommendation relevancy without compromising novelty.
Outcome: The proposed approach shows significant gains in both user satisfaction and exploration diversity.

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