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Dynamic language model representations for multi-objective reaction optimisation

Paper recorded by Signals 4 on 2026-09-10 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-10 on arXiv · recorded by Signals 4 on 2026-09-11

Category: cs.LG · 机器学习 · first seen 2026-09-11

Abstract

Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven approaches depend critically on how reaction components are represented. Established featurisations are either chemically uninformative, as with one-hot encodings, or, as with molecular descriptors, do not readily extend across chemically distinct com

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#76 most recent of 215 cs.LG papers we have recorded · ↑ newer: Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahe · ↓ older: Predicting Privacy Leakage from Weight Spectral Density
Cite this page: Dynamic language model representations for multi-objective reaction optimisation: the #76 most recent of 215 cs.LG papers we have recorded (as of 2026-09-10). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/dynamic-language-model-representations-for-multi-objective-reaction-optimisation.html
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