Papers by Yisheng Liu

1 papers
Reflection in the Dark: Exposing and Escaping the Black Box in Reflective Prompt Optimization (2026.acl-srw)

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Challenge: Automatic prompt optimization (APO) is a powerful paradigm for improving LLM performance without manual prompt engineering.
Approach: They propose a framework that decouples hypothesis generation from prompt rewriting . they propose VISTA framework that recovers accuracy to 87.57% on same defective seed .
Outcome: The proposed framework outperforms baselines on GSM8K and AIME2025 on a defective seed.

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