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Paper Citation Record · LEDGER

Active Learning on Synthons for Molecular Design

As of 20 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2505.12913.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.12913 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:28:06.229920Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 73b1da2c-ea7b-48eb-8f82-b0fbbb7f1282 · outbound

This paper cites Topological Similarity Search in Large Combinatorial Fragment Spaces.

Active Learning on Synthons for Molecular Design Topological Similarity Search in Large Combinatorial Fragment Spaces

Reference 1

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Source-reported events for the cited work

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Observation b57392e4-b41d-4cee-97ec-bf141a4952d3 · outbound

This paper cites Richard Bickerton, Gaia V.

Active Learning on Synthons for Molecular Design Richard Bickerton, Gaia V

Reference 2

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Observation 79b06890-2574-42be-974b-5cf1292b8a80 · outbound

This paper cites A Model to Search for Synthesizable Molecules.

Active Learning on Synthons for Molecular Design A Model to Search for Synthesizable Molecules

Reference 3

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Observation 6620cd19-000a-42d6-8aca-4b6b9bb7060b · outbound

This paper cites Carhart, Dennis H.

Active Learning on Synthons for Molecular Design Carhart, Dennis H

Reference 4

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Source-reported events for the cited work

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Observation c84211eb-76d3-4814-be9e-aca0c2bb3913 · outbound

This paper cites Shape-Aware Synthon Search (SASS) for virtual screening of synthon-based chemical spaces.

Active Learning on Synthons for Molecular Design Shape-Aware Synthon Search (SASS) for virtual screening of synthon-based chemical spaces

Reference 5

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Source-reported events for the cited work

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Observation 09155cde-f331-4446-acb6-18028e58ff84 · outbound

This paper cites SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints.

Active Learning on Synthons for Molecular Design SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints

Reference 6

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Observation 3a55e509-bbaa-4758-a60c-8161d4ceac3f · outbound

This paper cites REAL database, 2024.

Active Learning on Synthons for Molecular Design REAL database, 2024

Reference 7

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Source-reported events for the cited work

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Observation 967162e1-4e7f-4d75-8ec6-37ed545a8868 · outbound

This paper cites PyTorch Lightning , March 2019.

Active Learning on Synthons for Molecular Design PyTorch Lightning , March 2019

Reference 8

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Observation f3c1505e-e723-43cc-8ce1-1d574d7d6861 · outbound

This paper cites Haloperidol bound D2 dopamine receptor structure inspired the discovery of subtype selective ligands.

Active Learning on Synthons for Molecular Design Haloperidol bound D2 dopamine receptor structure inspired the discovery of subtype selective ligands

Reference 9

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Observation bfdb1ef7-3237-4243-b0da-25115ad4305a · outbound

This paper cites LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design.

Active Learning on Synthons for Molecular Design LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design

Reference 10

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Observation a81988db-12ec-4613-b3da-d89e6bd275e2 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Active Learning on Synthons for Molecular Design Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 11

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Observation 72f3f92b-32f2-4c42-86a8-59b123a70bbd · outbound

This paper cites an unresolved cited work.

Active Learning on Synthons for Molecular Design Unresolved cited work

Reference 12

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Observation 87f6bdbc-dec6-4820-9199-244557a19bb6 · outbound

This paper cites Generative Artificial Intelligence for Navigating Synthesizable Chemical Space.

Active Learning on Synthons for Molecular Design Generative Artificial Intelligence for Navigating Synthesizable Chemical Space

Reference 13

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Source-reported events for the cited work

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Observation 8b12ab0c-8447-430a-8caf-67a6888662b0 · outbound

This paper cites Accelerating high-throughput virtual screening through molecular pool-based active learning.

Active Learning on Synthons for Molecular Design Accelerating high-throughput virtual screening through molecular pool-based active learning

Reference 14

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Active Learning on Synthons for Molecular Design Unresolved cited work

Reference 15

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Observation 2fe2b9e5-8ffa-4662-8887-a0d7c44fd7a2 · outbound

This paper cites Greenman, Yunsie Chung, Shih-Cheng Li, David E.

Active Learning on Synthons for Molecular Design Greenman, Yunsie Chung, Shih-Cheng Li, David E

Reference 16

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Observation ec22c4fa-14ac-47af-8b26-3d7d7dbdea5e · outbound

This paper cites Patrick Walters.

Active Learning on Synthons for Molecular Design Patrick Walters

Reference 17

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Observation 236bbfdf-d41c-4f26-94f9-7e68bfd40862 · outbound

This paper cites Fast substructure search in combinatorial library spaces.

Active Learning on Synthons for Molecular Design Fast substructure search in combinatorial library spaces

Reference 18

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Observation 9d8f48be-31c3-4276-b2fc-e0cc2d9a1efb · outbound

This paper cites Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H.

Active Learning on Synthons for Molecular Design Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H

Reference 19

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Observation 9754520f-28d8-473f-ae83-e9423b7b6c95 · outbound

This paper cites Coley, and Jianzhu Ma.

Active Learning on Synthons for Molecular Design Coley, and Jianzhu Ma

Reference 20

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Observation e7f7d254-16e7-405b-8b22-364cd47dfe11 · outbound

This paper cites Irwin, and Brian K.

Active Learning on Synthons for Molecular Design Irwin, and Brian K

Reference 21

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This paper cites Mcule Database , accessed 18 Sep 2023.

Active Learning on Synthons for Molecular Design Mcule Database , accessed 18 Sep 2023

Reference 22

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Active Learning on Synthons for Molecular Design Unresolved cited work

Reference 23

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Observation c3450858-5e49-40fe-ae73-8cc0d805ff74 · outbound

This paper cites OpenEye Scientific Software , OpenEye toolkits (2022.1.1).

Active Learning on Synthons for Molecular Design OpenEye Scientific Software , OpenEye toolkits (2022.1.1)

Reference 24

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Observation 9b48d34e-c3dd-4042-bbd6-662b831b8b82 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Active Learning on Synthons for Molecular Design Pytorch: An imperative style, high-performance deep learning library

Reference 25

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This paper cites Rajapakse, Philippe G.

Active Learning on Synthons for Molecular Design Rajapakse, Philippe G

Reference 26

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Active Learning on Synthons for Molecular Design Open-source cheminformatics

Reference 27

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This paper cites On failure modes in molecule generation and optimization.

Active Learning on Synthons for Molecular Design On failure modes in molecule generation and optimization

Reference 28

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Observation a3f25050-5b4c-42c8-a44a-c484fcdc347d · outbound

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Active Learning on Synthons for Molecular Design Sadybekov, Anastasiia V

Reference 29

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Observation f1fd0a31-46db-4285-be7d-ca9d60b29b08 · outbound

This paper cites Maximum Common Substructure Searching in Combinatorial Make-on-Demand Compound Spaces.

Active Learning on Synthons for Molecular Design Maximum Common Substructure Searching in Combinatorial Make-on-Demand Compound Spaces

Reference 30

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Active Learning on Synthons for Molecular Design Automating drug discovery

Reference 31

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Active Learning on Synthons for Molecular Design Bronstein, and Renana Gershoni-Poranne

Reference 32

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Active Learning on Synthons for Molecular Design Wood, Svitlana Korolchuk, Natalie J

Reference 33

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Active Learning on Synthons for Molecular Design write newline

Reference 34

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Active Learning on Synthons for Molecular Design @esa (Ref

Reference 35

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Active Learning on Synthons for Molecular Design Unresolved cited work

Reference 36

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Active Learning on Synthons for Molecular Design Unresolved cited work

Reference 37

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Pith citing papers

No inbound Pith citation observations are available.