Papers by Zhichen Dong
Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary Signal (2026.findings-acl)
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| Challenge: | Recent training-free prompt optimizers treat performance as maximizing a single scalar score and ignore a second signal that the desired style is task dependent. |
| Approach: | They propose a semantic-entropy-based method that uses task uncertainty to guide prompt optimization by selecting high-entropicy candidates for creative tasks and low-energetic candidates for conservative ones. |
| Outcome: | The proposed method outperforms baselines on MT-Bench subsets and integrates easily into existing prompt optimizers. |
Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey (2024.naacl-long)
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| Challenge: | Large Language Models (LLMs) are now commonplace in conversation applications, but their misuse for generating harmful responses has raised serious societal concerns. |
| Approach: | They provide a comprehensive overview of recent studies covering attacks, defenses, and evaluations of Large Language Models (LLMs) . |
| Outcome: | The proposed review summarizes three aspects of LLM conversation safety: attacks, defenses, and evaluations. |