Ziyi Ni

Current defenses for Large Language Models (LLMs) often suffer from a ”memory gap”: parameter-modifying methods are computationally rigid, while inference-time filters cannot retain or reuse defense knowledge across interactions. To address this, we propose SafetyMem, a novel framework that secur...

Automated assessment of patent quality is increasingly important given the growth of patent filings and the adoption of AI-assisted drafting. Existing methods often rely on modular pipelines or generic detectors, resulting in fragmented decisions and limited integration across quality dimensions....

Long-horizon conversational agents have to manage ever-growing interaction histories that quickly exceed the finite context windows of large language models (LLMs). Existing memory frameworks provide limited support for temporally structured information across hierarchical levels, often leading t...