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22:end if 23:end for Algorithm S2TAMOTest-Time Algorithm Require: Pre-trainedTAMOmodel, new task τtest, query budget T , initial history set Dh 0 :={x h, yh} (with random samples if empty), 1:D h ← D h 0 ▷Initialize the history set 2:P ← {y · 2020

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cs.LG 1

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2025 1

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UNVERDICTED 1

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In-Context Multi-Objective Optimization

cs.LG · 2025-12-11 · unverdicted · novelty 7.0

TAMO is a transformer policy pretrained with RL to perform amortized multi-objective optimization in-context, delivering 50-1000x faster proposals while matching Pareto quality on benchmarks.

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  • In-Context Multi-Objective Optimization cs.LG · 2025-12-11 · unverdicted · none · ref 6

    TAMO is a transformer policy pretrained with RL to perform amortized multi-objective optimization in-context, delivering 50-1000x faster proposals while matching Pareto quality on benchmarks.