Papers by Jialing He

2 papers
Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework (2026.findings-acl)

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Challenge: Existing studies on how SAEs derive most fine-grained latent features for safety remain unexplored.
Approach: They propose a framework for interpreting SAE features in safety-critical domains . they train a suite of SAEs with human-readable explanations and systematic evaluations based on pornography, politics, violence, and terror .
Outcome: The proposed framework reduces interpretation cost by 55% and improves safety-critical features.
S-RAG: A Novel Audit Framework for Detecting Unauthorized Use of Personal Data in RAG Systems (2025.acl-long)

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Challenge: Retrieval-Augmented Generation (RAG) systems rely on external data for accurate and context-specific responses.
Approach: They propose a framework that enables users to determine whether their textual data has been utilized in RAG systems even in black-box settings with no prior system knowledge.
Outcome: The proposed framework achieves an improvement in Accuracy by 19.9% while maintaining strong performance under adversarial defenses.

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