Author

Haebeom Lee

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#artificial intelligence Feb 2026

GFlowPO: Generative Flow Network as a Language Model Prompt Optimizer

This work proposes GFlowPO, a probabilistic prompt optimization framework that casts prompt search as a posterior inference problem over latent prompts regularized by a meta-prompted reference-LM prior and consistently outperforms recent discrete prompt optimization baselines.

Junmo Cho, Suhan Kim, Sangjune An et al. · arXiv.org · 0 citations

#machine learning Open access Oct 2023

Delta-AI: Local objectives for amortized inference in sparse graphical models

A new algorithm for amortized inference in sparse probabilistic graphical models (PGMs) is presented that enables off-policy training but avoids the need to instantiate all the random variables for each parameter update, thus speeding up training considerably.

J. Falet, Haebeom Lee, Esmeralda S. Whitammer et al. · International Conference on... · 9 citations