Reinforcement learning on the discrete composition channel of a crystal generator; validated gains and reward hacking
Read the original at arxiv.org→arXiv:2610.03880v1 Announce Type: new Abstract: Inverse materials design is a long-standing goal of computational materials discovery. Generative models for crystalline materials are typically trained to match the...
Original headline: "Reinforcement Learning on the Discrete Composition Channel of a Crystal Generator: Validated Gains and Reward Hacking"
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- Oct 6, 04:00 UTC arXiv cs.LG lead source Reinforcement Learning on the Discrete Composition Channel of a Crystal Generator: Validated Gains and Reward Hacking