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multi-objective optimization

topic3 events
papersTODAY 04:00 UTC

arXiv paper proposes Thompson sampling method for multi-objective public media decisions

A revised arXiv paper introduces a contextual scalarisation Thompson sampling approach for recommender systems that must balance several competing goals at once. The authors use public service media editorial decisions as a motivating case, where audience reach, cultural values, public service duties, and operational limits all compete. The method aims to support decision-making when objectives cannot be easily reduced to a single score.

recommender-systems/multi-objective/research/public-media
papersTODAY 04:00 UTC

Value-Guided Preference Distillation Proposed for Long-Horizon Dialogue Alignment

A new arXiv paper argues that aligning multi-turn dialogue agents by matching turn-level human preferences is a poor proxy for long-term outcomes and is vulnerable to reward hacking. The authors recast long-horizon dialogue optimization as a multi-objective problem and propose distilling dense behavioral signals into value guidance for preference-based training. The method is presented as a way to optimize sparse end goals more reliably without directly optimizing them.

alignment/dialogue/preference-optimization/research
papersTODAY 04:00 UTC

Multi-Objective Hyperparameter Search Using Damped Gauss-Newton Optimization

A new arXiv paper reframes hyperparameter optimization as a numerical optimization problem rather than a sequence of independent trials. The authors propose a multi-objective, damped Gauss-Newton search method that estimates a finite-difference-based model of the objective landscape. The work is a replacement cross-list submission on arXiv's machine learning section.

hyperparameter-optimization/optimization/research/arxiv