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Traditional methods rely on expert knowledge and incur substantial time and cost. In this study, we introduce a novel 2-stage end-to-end deep learning approach for predicting astrochemical reaction products, marking the first application of these techniques in this field. Our method comprises 2 primary phases: a generative phase leveraging a graph encoder and transformer architecture for the generation of potential reaction products, and a contrastive learning-based phase for re-ranking the potential products. We rigorously evaluated the performance of our approach using the ChemiVerse dataset. Experimental results show notable accuracy rates of 82.4% (Top-1), 91.4% (Top-3), 93.0% (Top-5), and 93.7% (Top-10). This study demonstrates the feasibility and effectiveness of using advanced deep learning techniques for end-to-end astrochemical reaction prediction.<\/jats:p>","DOI":"10.34133\/icomputing.0118","type":"journal-article","created":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T07:11:01Z","timestamp":1743577861000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":2,"title":["A Two-Stage End-to-End Deep Learning Approach for Predicting Astrochemical Reactions"],"prefix":"10.34133","volume":"4","author":[{"given":"Jiawei","family":"Wang","sequence":"first","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0217-3773","authenticated-orcid":true,"given":"Yanan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haili","family":"Bu","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Lu","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manni","family":"Duan","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghui","family":"Quan","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Qiu","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, Zhejiang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"221","published-online":{"date-parts":[[2025,5,15]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","unstructured":"Yamamoto S. 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