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Paper Citation Record · LEDGER

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation

As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2508.16521.

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

pith.paper-citation-record.v1
2508.16521 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:21:56.405213Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:02:31.450585Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 59c5560f-9fd4-48c5-b0e1-6f22a3f55db7 · outbound

This paper cites Denoising diffusion probabilistic models.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Denoising diffusion probabilistic models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8003a58a-66da-4060-9bb8-94e2e064fe06 · outbound

This paper cites Generative adversarial networks.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Generative adversarial networks

Reference 2

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Observation a09c2882-7f13-401f-bed2-082403e74bfd · outbound

This paper cites An introduction to variational autoencoders.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation An introduction to variational autoencoders

Reference 3

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 48511b6c-a822-4f6d-b203-3a0e0bd81d47 · outbound

This paper cites E (n) equivariant graph neural networks.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation E (n) equivariant graph neural networks

Reference 4

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Observation 2a1ee6e4-4a8c-451f-bb4c-f352307364b3 · outbound

This paper cites Equiformer: Equivariant graph attention transformer for 3d atomistic graphs.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Equiformer: Equivariant graph attention transformer for 3d atomistic graphs

Reference 5

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Source-reported events for the cited work

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Observation f6950ed4-ea64-4dfa-9692-30859c40d6bd · outbound

This paper cites Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 60882a56-f715-4aa8-9255-e13fc132388c · outbound

This paper cites Geodiff: A geometric diffusion model for molecular conformation generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Geodiff: A geometric diffusion model for molecular conformation generation

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f73b0878-ded7-42d0-b7ee-296172f05fe0 · outbound

This paper cites Torsional diffusion for molecular conformer generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Torsional diffusion for molecular conformer generation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation da686054-7b46-42d9-bb9f-5c1a9df39bd6 · outbound

This paper cites Equivariant diffusion for molecule generation in 3D.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Equivariant diffusion for molecule generation in 3D

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7c68699f-2541-422a-bff2-11b0b5a231be · outbound

This paper cites Learning to summarize with human feedback.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Learning to summarize with human feedback

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0b1a01b4-71a4-4b49-b10b-1a95a36bf90e · outbound

This paper cites Markov decision processes.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Markov decision processes

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7ae4f8e0-dfbc-4821-8e5a-8cee29c1c505 · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 43e2ea82-d732-46f9-a1f9-432f10096605 · outbound

This paper cites Geometric latent diffusion models for 3d molecule generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Geometric latent diffusion models for 3d molecule generation

Reference 13

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b84a42dc-b9c8-450d-bf86-fa2e802bebdf · outbound

This paper cites Unigem: A unified approach to generation and property prediction for molecules.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Unigem: A unified approach to generation and property prediction for molecules

Reference 14

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verified fuzzy
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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d04bc705-8dcd-47bb-a13b-b29d81b27a75 · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Quantum chemistry structures and properties of 134 kilo molecules

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation ba4e8e85-a03a-46aa-bcf3-ed87c5eca5ab · outbound

This paper cites Geom, energy-annotated molecular conformations for property prediction and molecular generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Geom, energy-annotated molecular conformations for property prediction and molecular generation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:21:56.775755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9d63de14-de69-4e69-9bb3-940eafb9bed6 · outbound

This paper cites Automatic chemical design using a data-driven continuous representation of molecules.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Automatic chemical design using a data-driven continuous representation of molecules

Reference 17

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 605556e8-1c3d-4f86-90f1-38f0a55629a0 · outbound

This paper cites Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d99e3993-a792-4c29-8ee4-ddd284ea6037 · outbound

This paper cites Symphony: Symmetry-equivariant point- centered spherical harmonics for molecule generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Symphony: Symmetry-equivariant point- centered spherical harmonics for molecule generation

Reference 19

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Source-reported events for the cited work

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Observation 400b8205-f5ba-42a3-ba29-558396df828b · outbound

This paper cites Equivariant neural diffusion for molecule generation.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Equivariant neural diffusion for molecule generation

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation bb31cae0-ba70-42b6-8e88-6591b2bf674c · outbound

This paper cites Equivariant 3d-conditional diffusion model for molecular linker design.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Equivariant 3d-conditional diffusion model for molecular linker design

Reference 21

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 82fee1aa-7f38-4100-8909-7c084aefa69b · outbound

This paper cites A survey of large language models.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation A survey of large language models

Reference 22

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9e804304-7729-4b90-b6d7-a06dbeb6817b · outbound

This paper cites Training diffusion models with reinforcement learning.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Training diffusion models with reinforcement learning

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 32da9c0d-9601-4a35-9f94-41007b102f63 · outbound

This paper cites Reinforcement learning for fine-tuning text-to-image diffusion models.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Reinforcement learning for fine-tuning text-to-image diffusion models

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b868e884-e9b3-4dde-a987-d61e29397bbc · outbound

This paper cites A multi-composition reinforcement learning framework for isomer discovery in 3d.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation A multi-composition reinforcement learning framework for isomer discovery in 3d

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1699e3d1-0870-4fe3-9fad-74ef57e4dbe1 · outbound

This paper cites Graph diffusion policy optimization.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Graph diffusion policy optimization

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 535054db-274c-4aed-8cc6-c12c83f8c04f · outbound

This paper cites Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-05T17:21:56.587033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 51c8f597-a087-415f-8bcc-fe610c94eed1 · outbound

This paper cites Diffusion-based molecule generation with informative prior bridges.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Diffusion-based molecule generation with informative prior bridges

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e1a8f09a-9d5e-4033-9baf-22d6b9d47789 · outbound

This paper cites Unified generative modeling of 3d molecules via bayesian flow networks.����� �������� ����������������, 2024.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Unified generative modeling of 3d molecules via bayesian flow networks.����� �������� ����������������, 2024

Reference 29

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raw_fallback, observed 2026-08-05T17:21:56.554760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T17:21:56.376121Z digest=sha256:16ed477e540a511b8d3d57aa676592128c41565a85053a802cd3a7c5571130db

Observation 8c14c446-702d-4647-b939-f0f4e4608c28 · outbound

This paper cites Cormorant: Covariant molecular neural networks.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Cormorant: Covariant molecular neural networks

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-05T17:21:56.535842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T17:21:56.380543Z digest=sha256:bd051d69ae8ed196d3d0eef8e632349537635f5fc6c24ff4b72498f8d73f0196

Observation 621e3aa1-ef17-4861-add5-1d2100aa62da · outbound

This paper cites E (n) equivariant normalizing flows.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation E (n) equivariant normalizing flows

Reference 31

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raw_fallback, observed 2026-08-05T17:21:56.516538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T17:21:56.384778Z digest=sha256:844b0b4173037e28cc46eb3a46d82c7a8cdd7bf5013af85f34497846cbcdc3fa

Observation 7ec4fe9c-a515-4ce1-8521-fefe2dc2067e · outbound

This paper cites Top-n: Equivariant set and graph generation without exchangeability.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation Top-n: Equivariant set and graph generation without exchangeability

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T17:21:56.389104Z digest=sha256:d101936ca025df87e07bf20dc1b61f0cd2a3a5321d0f815659f97ca1d3379916

Observation 3cf22999-4de3-4976-92ce-dd7f8046ec94 · outbound

This paper cites This captures both the intermediate states �t and the final molecular structure ��� ��.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation This captures both the intermediate states �t and the final molecular structure ��� ��

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T17:21:56.395184Z digest=sha256:6b160a1a1c4ebf369c3856a96a76b4c4462896ad97f481bd790e1bb7e4f28605

Observation d5b19f47-830b-43a0-82b7-9e7de443c407 · outbound

This paper cites These values serve as scalar rewards ���� ��.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation These values serve as scalar rewards ���� ��

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-05T17:21:56.464934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0942e167-7129-48db-a249-2885782b9579 · outbound

This paper cites The importance sampling ratio �k t ��� is computed using log- likelihood scores from Section 4.5.

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation The importance sampling ratio �k t ��� is computed using log- likelihood scores from Section 4.5

Reference 35

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Pith citing papers

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Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning cites this paper.

Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation

Reference 25

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