Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
A novel unified operator is introduced that combines several regularized RL operators into a general framework that better targets peakier sampling distributions and is named trajectory general mellowmax (TGM), which is shown to identify higher quality, diverse candidates than baselines in both synthetic and real-world tasks.
Marco Jiralerspong, Esther Derman, Danilo Vucetic et al.
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