Papers by Yuhan Dong
ShieldHead: Decoding-time Safeguard for Large Language Models (2025.findings-acl)
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| Challenge: | Recent advances in LLM-based moderation methods have demonstrated remarkable promise in identifying safety risks associated with both inputs and outputs in human-AI interactions. |
| Approach: | They propose to learn a classification head on the last-layer hidden states of a dialogue model and use it to detect harmful content. |
| Outcome: | The proposed framework is 300 faster (**1ms**) than previous LLM-based moderation models with 99% less parameters than LlamaGuard. |