{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/multi-resolution-autoregressive-graph-to","title":"Hierarchical Graph-to-Graph Translation for Molecules","arxiv_id":"1907.11223","date":"2019-06-11","proceeding":null,"authors":["Wengong Jin","Regina Barzilay","Tommi Jaakkola"],"abstract":"The problem of accelerating drug discovery relies heavily on automatic tools to optimize precursor molecules to afford them with better biochemical properties. Our work in this paper substantially extends prior state-of-the-art on graph-to-graph translation methods for molecular optimization. In particular, we realize coherent multi-resolution representations by interweaving the encoding of substructure components with the atom-level encoding of the original molecular graph. Moreover, our graph decoder is fully autoregressive, and interleaves each step of adding a new substructure with the process of resolving its attachment to the emerging molecule. We evaluate our model on multiple molecular optimization tasks and show that our model significantly outperforms previous state-of-the-art baselines.","url_abs":"https://arxiv.org/abs/1907.11223v2","url_pdf":"https://arxiv.org/pdf/1907.11223v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"multi-resolution-autoregressive-graph-to","repo_url":"https://github.com/wengong-jin/hgraph2graph","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"drug-discovery","task_name":"Drug Discovery"},{"task_slug":"graph-to-graph-translation","task_name":"Graph-To-Graph Translation"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/drug-discovery-on-drd2","task":"Drug Discovery","dataset":"DRD2","model":"HierG2G","rank_in_archive_order":1,"of":1,"metrics":{"Diversity":"0.192","Success":"85.9%"},"uses_additional_data":false},{"leaderboard":"/sota/drug-discovery-on-qed","task":"Drug Discovery","dataset":"QED","model":"HierG2G","rank_in_archive_order":1,"of":1,"metrics":{"Diversity":"0.477","Success":"76.9%"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1907.11223","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}