arxiv
PublishedMay 26, 2026 at 4:00 AM
—neutral
Active Query Synthesis for Preference Learning
Publisher summary· verbatim
arXiv:2605.26072v1 Announce Type: new Abstract: Efficient learning of user preferences is crucial for many modern decision making systems but typically requires costly labeled data. Active learning reduces this cost, yet standard methods are computationally expensive due to pool-based evaluation. Fu
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Originally published on arxiv ↗