Papers by Haohua Wang

2 papers
Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory (2026.acl-long)

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Challenge: Existing methods for retrieving historical messages are based on similarity-based mechanisms.
Approach: They propose a system that integrates System-1 similarity search with a complementary System-2 mechanism, termed Global Selection.
Outcome: The proposed framework achieves state-of-the-art on long-term memory benchmarks and 93.9 on LoCoMo and 91.6 on LongMemEval-S.
Activation-Guided Local Editing for Jailbreaking Attacks (2026.acl-long)

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Challenge: Existing methods for jailbreaking Large Language Models (LLMs) are limited and produce incoherent or unreadable inputs.
Approach: They propose a two-stage framework that performs a one-shot, scenario-based generation of context and rephrases the original malicious query to obscure its harmful intent.
Outcome: The proposed framework achieves state-of-the-art Attack Success Rate, with gains of up to 37.74% over the strongest baseline, and excellent transferability to black-box and large-scale models.

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