arXiv AI July 10, 2026 By Sutanay Choudhury, Anwesha Banerjee, Udishnu Sanyal, Jorin Dawidowicz, Chiezugolum Ijeoma Odilinye, Jesun Firoz, Liney Arnadottir, Simone Raugei, Johannes Lercher, Arnab Dutta

Reaction-network reasoning with frontier models for experimentally confirmed catalyst-selectivity hypotheses

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arXiv:2607. 08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error experimentation and computationally intensive screening.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

llms

arXiv Machine Learning

Jul 21

ChemFusion: A Multimodal Cross-Attention Network for Reaction Yield Prediction

arXiv:2607. 17033v1 Announce Type: new Abstract: Forecasting the outcomes of transition-metal-catalyzed reactions is notoriously complex due to the interplay of diverse physical and chemical variables.

By Qiwei Han, Chi Zhou

multimodal safety

arXiv Machine Learning

Jul 1

ReactionAtlas: Ab origine exploration of chemical reaction networks with machine learning

arXiv:2606. 30778v1 Announce Type: new Abstract: Mapping a chemical reaction network, the graph of minima and transition states (TS) and the elementary reactions connecting them, is the natural language of chemistry, from catalysis to combustion to the origin of life.

By Stefan Gugler, Max Eissler, Khaled Kahouli, Klaus-Robert M\"uller

arXiv Machine Learning

Aug 7

RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction

arXiv:2608. 06259v1 Announce Type: new Abstract: Reaction yield prediction remains challenging because labeled data are scarce and reaction space is both combinatorially large and sparsely populated, limiting the generalization of existing reaction representations.

By Yiting Zheng, Cheng Fang, Anthony Donofrio, Haote Li

diffusion fine-tuning benchmarks

arXiv AI

Jun 8

Autonomous computational catalysis through an agentic research system

arXiv:2601. 13508v4 Announce Type: replace-cross Abstract: Autonomous agents are beginning to transform scientific research from tool-assisted workflows toward self-sustaining discovery processes.

By Honghao Chen, Jiangjie Qiu, Yi Shen Tew, Xiaonan Wang

agents

arXiv AI

Jun 30

Interpretable Inverse Design of Metal-Organic Frameworks with Large Language Model Agents

arXiv:2606. 29459v1 Announce Type: cross Abstract: Inverse design of metal-organic frameworks (MOFs) requires searching a combinatorially vast space where property labels are expensive and most machine-learning models reveal little about why a structure succeeds.

By Kyungmin Nam, Seunghee Han, Jihan Kim

llms agents

arXiv Machine Learning

Jul 15

Learning Mechanistic Reasoning for Chemical Reactions with Large Language Models

arXiv:2607. 12771v1 Announce Type: new Abstract: Reaction mechanisms consist of the step-by-step sequences of elementary reactions that explain chemical transformations.

By Xingyu Dang, Haocheng Tang, Junmei Wang, Yanjun Li

llms fine-tuning benchmarks safety

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ChemFusion: A Multimodal Cross-Attention Network for Reaction Yield Prediction

ReactionAtlas: Ab origine exploration of chemical reaction networks with machine learning

RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction

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Learning Mechanistic Reasoning for Chemical Reactions with Large Language Models