active learning
active-learning-7fe49f56·2 events·first seen 22d agoAliases: active learning
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Active Query Synthesis for Preference Learning via Mutual Information Maximization
This paper introduces Info-Synth, an active query synthesis framework for preference learning that generates optimal pairwise queries by maximizing a mutual information objective in continuous space, bypassing the computational cost of pool-based evaluation. A confidence-aware response model is proposed to handle ambiguous comparisons between nearly identical or highly dissimilar items. Two finite-pool extensions (Pair M-dist and Pair Opt-dist) are also introduced. The framework is validated on synthetic preference tasks, text summarization datasets, and robotic controller tuning.
Review: Generative Models, Multimodal Learning, and Closed-Loop Workflows in Inverse Materials Design
This arxiv review surveys recent advances in generative modeling for inverse materials design, covering variational autoencoders, normalizing flows, autoregressive models, and diffusion models applied to crystalline solid discovery. It examines how multimodal learning fuses crystal structures, thermodynamic data, spectroscopy, microscopy, and scientific text into transferable chemical-space representations. The paper also reviews closed-loop design pipelines integrating conditional generation with Bayesian optimization, reinforcement learning, and active learning, and identifies recurring failure modes including surrogate exploitation, diversity collapse, and the stability-synthesizability gap.