mlsanityData to 14 Oct 2026

Survey on Recent Progress of AI for Chemistry: Methods, Applications, and Opportunities

arXiv 2502.17456 ↗First posted 9 Feb 2025physics.chem-ph cs.AI cs.LGcited by 3

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Abstract (arXiv)

The development of artificial intelligence (AI) techniques has brought revolutionary changes across various realms. In particular, the use of AI-assisted methods to accelerate chemical research has become a popular and rapidly growing trend, leading to numerous groundbreaking works. In this paper, we provide a comprehensive review of current AI techniques in chemistry from a computational perspective, considering various aspects in the design of methods. We begin by discussing the characteristics of data from diverse sources, followed by an overview of various representation methods. Next, we review existing models for several topical tasks in the field, and conclude by highlighting some key challenges that warrant further attention.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 65 of its 208 references that are in the map. First posted on arXiv 9 Feb 2025.

Builds on

65 of 208 references.

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50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025RxnCaption: Reformulating Reaction Diagram Parsing as Visual Prompt Guided Captioningcited by 3
  2. 2026Molecular Identifier Visual Prompt and Verifiable Reinforcement Learning for Chemical Reaction Diagram Parsingcited by 2
  3. 2026MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsingcited by 0