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Do We Really Need to Approach the Entire Pareto Front in Many-Objective Bayesian

BACKGROUND
2 SIGNALSFIRST DETECTED 13 April 2026
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20 May
MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization

arXiv:2605.19330v1 Announce Type: new Abstract: LLM agents organize behavior through skills - structured natural-language specifications governing how an agent reasons, retrieves,

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23 Mar
PA2D-MORL: Pareto Ascent Directional Decomposition based Multi-Objective Reinforcement Learning

arXiv:2603.19579v1 Announce Type: new Abstract: Multi-objective reinforcement learning (MORL) provides an effective solution for decision-making problems involving conflicting

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11 May
Open-Ended Task Discovery via Bayesian Optimization

arXiv:2605.07572v1 Announce Type: new Abstract: When applying Bayesian optimization (BO) to scientific workflow, a major yet often overlooked source of uncertainty is the task

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4 Aug
DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization

arXiv:2608.00641v1 Announce Type: new Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks

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9 Jul
Deep Reinforcement Learning for Reliability Based Bi-Objective Portfolio Optimization

arXiv:2607.06610v1 Announce Type: cross Abstract: Portfolio optimization under uncertainty is inherently a multi-objective decision problem involving complex interactions among

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11 May
From Feasible to Practical: Pareto-Optimal Synthesis Planning

arXiv:2605.07521v1 Announce Type: new Abstract: Current computer-aided synthesis planning (CASP) methods often treat retrosynthesis as solved once a single feasible route is

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