Paper Citation Record · LEDGER

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules

As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2411.10821.

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

pith.paper-citation-record.v1
2411.10821 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

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measured 61 of 61 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:39:32.695975Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:39:33.483986Z

Reference resolution

60 of 60 outbound references displayed

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External citation measurements

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Outbound references

Observation 784a219e-a42d-4f94-b2c1-48f176518552 · outbound

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

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Geom, energy- annotated molecular conformations for property predic- tion and molecular generation,

Reference 1

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Observation 0bb9b14e-874f-4edd-b7ee-7816e3e81454 · outbound

This paper cites Scibert: A pretrained language model for scientific text,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Scibert: A pretrained language model for scientific text,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.200144Z

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Observation f57dc782-e90d-40af-9a4a-bf5f3a4a86fe · outbound

This paper cites Molecule joint auto-encoding: Trajectory pretraining with 2d and 3d diffusion,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molecule joint auto-encoding: Trajectory pretraining with 2d and 3d diffusion,

Reference 3

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Observation 5a30ed8e-a9d3-4b73-8512-57a43e5d43c9 · outbound

This paper cites Ba-gnn: On learning bias-aware graph neural network,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Ba-gnn: On learning bias-aware graph neural network,

Reference 4

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Observation d0322f63-a740-4a08-a05d-6cbe524d799f · outbound

This paper cites Unifying molecular and tex- tual representations via multi-task language modelling,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Unifying molecular and tex- tual representations via multi-task language modelling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.161609Z

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Observation fb124113-f1f2-4556-af8b-053666647ea9 · outbound

This paper cites Translation between molecules and natural language,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Translation between molecules and natural language,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.147745Z

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Observation 07a6a5e5-71c8-47d6-898f-61992516e665 · outbound

This paper cites Text2mol: Cross-modal molecule retrieval with natural language queries,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Text2mol: Cross-modal molecule retrieval with natural language queries,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.134001Z

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Observation d7cca178-291a-495f-a92a-f99a389b90b8 · outbound

This paper cites Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Reference 8

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Observation 11c940b5-a91f-4c26-95c5-52834fabc4c8 · outbound

This paper cites Fractional denoising for 3d molecular pre-training,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Fractional denoising for 3d molecular pre-training,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.120290Z

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Observation 4833ddaf-1e15-4203-85a9-0f3886425f4b · outbound

This paper cites Neural message passing for quantum chemistry,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Neural message passing for quantum chemistry,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.108682Z

Source-reported events for the cited work

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Observation 3f5c5e70-ff21-4d49-98d4-ff26d179bd17 · outbound

This paper cites Audioclip: Extending clip to image, text and audio,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Audioclip: Extending clip to image, text and audio,

Reference 11

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Observation 21921e31-f2f4-4c76-92bd-7fc548ee3694 · outbound

This paper cites Inchi, the iupac international chem- ical identifier,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Inchi, the iupac international chem- ical identifier,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.087230Z

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Observation bc945113-8ea1-49dc-a692-0c884e322fa8 · outbound

This paper cites Pubchem in 2021: new data content and improved web interfaces,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Pubchem in 2021: new data content and improved web interfaces,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.074363Z

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Observation b5b1693c-5dec-4ae0-bc0d-c002052a623c · outbound

This paper cites Adam: A method for stochastic optimization,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Adam: A method for stochastic optimization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.062149Z

Source-reported events for the cited work

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Observation 0d379baa-3915-4d27-a7aa-a5d643871adf · outbound

This paper cites Protein– ligand pose and affinity prediction: Lessons from d3r grand challenge 3,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Protein– ligand pose and affinity prediction: Lessons from d3r grand challenge 3,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.049717Z

Source-reported events for the cited work

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Observation 4c795c50-17c7-4bf5-bf85-eab0e6acca31 · outbound

This paper cites Self-referencing embedded strings (selfies): A 100% robust molecular string representation,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Self-referencing embedded strings (selfies): A 100% robust molecular string representation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.036784Z

Source-reported events for the cited work

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Observation 654443ea-5fa3-4fc7-8ea5-4e8707969a03 · outbound

This paper cites Rdkit: A software suite for chemin- formatics, computational chemistry, and predictive mod- eling,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Rdkit: A software suite for chemin- formatics, computational chemistry, and predictive mod- eling,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.023885Z

Source-reported events for the cited work

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Observation 431c0095-ecea-448f-b47e-78aad52deffe · outbound

This paper cites Towards 3D Molecule-Text Interpretation in Language Models.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Towards 3D Molecule-Text Interpretation in Language Models

Reference 18

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Observation e4fe3cdf-58a0-40b6-ab2a-8e40b5734ccc · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Rouge: A package for automatic evaluation of summaries,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T19:20:38.210295Z

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Observation 1ecb463f-038e-41fb-92e9-da7b4ff84929 · outbound

This paper cites Git-mol: A multi- modal large language model for molecular science with graph, image, and text,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Git-mol: A multi- modal large language model for molecular science with graph, image, and text,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:39.004768Z

Source-reported events for the cited work

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Observation cf4821a2-029f-49cc-9a59-63d5d3f662d7 · outbound

This paper cites A group symmetric stochastic differential equation model for molecule multi-modal pretraining,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules A group symmetric stochastic differential equation model for molecule multi-modal pretraining,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.993875Z

Source-reported events for the cited work

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Observation d7e28414-2e2f-4556-b15d-fd6461f802f3 · outbound

This paper cites Molecular geometry pre- training with se (3)-invariant denoising distance match- ing,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molecular geometry pre- training with se (3)-invariant denoising distance match- ing,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.982548Z

Source-reported events for the cited work

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Observation d868f5ac-3ed8-4828-8cf6-244e3a45b8cc · outbound

This paper cites Multi-modal molecule structure–text model for text-based retrieval and editing,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Multi-modal molecule structure–text model for text-based retrieval and editing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.971090Z

Source-reported events for the cited work

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Observation 61f810fc-c411-4691-bbd0-122feb8cbe73 · outbound

This paper cites Pre-training molecular graph representation with 3d geometry,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Pre-training molecular graph representation with 3d geometry,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.960253Z

Source-reported events for the cited work

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Observation 0057092a-48a2-4879-9c4f-44b3b5ded0a8 · outbound

This paper cites MolXPT: Wrapping molecules with text for generative pre-training,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules MolXPT: Wrapping molecules with text for generative pre-training,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.948999Z

Source-reported events for the cited work

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Observation df7dbe5e-209b-4467-a816-4f906c6fc97d · outbound

This paper cites Molca: Molecular graph- language modeling with cross-modal projector and uni- modal adapter,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molca: Molecular graph- language modeling with cross-modal projector and uni- modal adapter,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.937885Z

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Observation 8e4f9449-f57f-4d18-847d-a275f9d90ee9 · outbound

This paper cites Clip4clip: An empirical study of clip for end to end video clip retrieval and captioning,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Clip4clip: An empirical study of clip for end to end video clip retrieval and captioning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.926174Z

Source-reported events for the cited work

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Observation 5ec09571-e29e-4e2e-9bcf-6a17ad292ac3 · outbound

This paper cites One transformer can understand both 2d & 3d molecular data,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules One transformer can understand both 2d & 3d molecular data,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.913449Z

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Observation 00391575-5c8c-4357-bedc-7fc27fad48ae · outbound

This paper cites MolFM: A Multimodal Molecular Foundation Model.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules MolFM: A Multimodal Molecular Foundation Model

Reference 29

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Observation e35640b5-cd54-453e-880e-1d366aeb6dd5 · outbound

This paper cites Pubchemqc project: a large-scale first-principles electronic structure database for data-driven chemistry,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Pubchemqc project: a large-scale first-principles electronic structure database for data-driven chemistry,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.899990Z

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Observation 07347fab-3d57-48ba-bf40-65e45c714726 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Bleu: a method for automatic evaluation of machine translation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.887345Z

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Observation 12b00e99-a270-4138-af1a-45c57233e634 · outbound

This paper cites Local den- sity functional theory of atoms and molecules,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Local den- sity functional theory of atoms and molecules,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.874320Z

Source-reported events for the cited work

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Observation 5f35fb7d-d583-4c33-8c97-43cbdf92e844 · outbound

This paper cites Biot5: Enriching cross-modal integration in biology with chemical knowledge and natural language associations,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Biot5: Enriching cross-modal integration in biology with chemical knowledge and natural language associations,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.860303Z

Source-reported events for the cited work

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Observation 664ec652-1687-48ae-8813-39dba14a6557 · outbound

This paper cites Data-driven strategies for accelerated materials design,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Data-driven strategies for accelerated materials design,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.849024Z

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Observation bab67beb-7c95-491b-bcad-686f1cb14363 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Learning transferable visual models from natural language supervision,

Reference 35

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Source-reported events for the cited work

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Observation 4ff10bbe-1244-440c-a1e4-80e491affd61 · outbound

This paper cites Quantum chemistry structures and prop- erties of 134 kilo molecules,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Quantum chemistry structures and prop- erties of 134 kilo molecules,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.830621Z

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Observation e98258d0-b0f4-4b28-b6d2-0d846b7ba202 · outbound

This paper cites Recent advances and applications of machine learning in solid-state materials science,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Recent advances and applications of machine learning in solid-state materials science,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.820877Z

Source-reported events for the cited work

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Observation 5475bfa9-c2fc-4a3c-b07b-4f4a59d45e1d · outbound

This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Equivariant message passing for the prediction of tensorial properties and molecular spectra,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.810756Z

Source-reported events for the cited work

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Observation 21e40117-e7d9-40e2-b689-52065f8d9f0a · outbound

This paper cites Schnet–a deep learn- ing architecture for molecules and materials,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Schnet–a deep learn- ing architecture for molecules and materials,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.800210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b2f8101a-e4e5-4803-8048-def834b38304 · outbound

This paper cites Enhancing activity prediction models in drug discovery with the ability to understand human language,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Enhancing activity prediction models in drug discovery with the ability to understand human language,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.666043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 49b1c0fc-74a7-42fc-b7a0-3601c7ce632c · outbound

This paper cites Molecular property pre- diction: recent trends in the era of artificial intelligence,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molecular property pre- diction: recent trends in the era of artificial intelligence,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.654736Z

Source-reported events for the cited work

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Observation cf1c8223-8d4e-452c-9705-d8234e679dc7 · outbound

This paper cites Flava: A foundational language and vision alignment model,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Flava: A foundational language and vision alignment model,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.644084Z

Source-reported events for the cited work

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Observation 26927de6-27b8-4cd4-8941-6d0c48fe1323 · outbound

This paper cites 3d infomax improves gnns for molecular property prediction,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules 3d infomax improves gnns for molecular property prediction,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.632292Z

Source-reported events for the cited work

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Observation b9615b06-a574-40d3-9203-73295e158821 · outbound

This paper cites A deep learning approach to antibiotic discovery,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules A deep learning approach to antibiotic discovery,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.621232Z

Source-reported events for the cited work

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Observation 478f2194-17f5-4429-ac46-f0aa68fcd374 · outbound

This paper cites A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T19:20:38.303106Z

Source-reported events for the cited work

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Observation 3c089a0d-4d93-49ec-a995-cc46a8567ba6 · outbound

This paper cites Mollm: A unified language model to integrate biomedical text with 2d and 3d molecular representations,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Mollm: A unified language model to integrate biomedical text with 2d and 3d molecular representations,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.610308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ff2bda54-c621-4cce-8426-24dee30475bb · outbound

This paper cites Improving molecular contrastive learning via faulty negative mitigation and decomposed fragment contrast,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Improving molecular contrastive learning via faulty negative mitigation and decomposed fragment contrast,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.599264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5d3c6ae6-084b-4dd2-b2e9-4704c429b2e2 · outbound

This paper cites Molecu- lenet: a benchmark for molecular machine learning,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molecu- lenet: a benchmark for molecular machine learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.588662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b6fb35c-5ac5-47df-adca-fadd5de36445 · outbound

This paper cites De- coupled self-supervised learning for graphs,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules De- coupled self-supervised learning for graphs,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.577004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 40534e3f-b1fc-408a-b978-f56df037d690 · outbound

This paper cites Learning how to propagate messages in graph neural networks,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Learning how to propagate messages in graph neural networks,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.566984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fbd27045-994b-4e4a-b129-53f57e3dabff · outbound

This paper cites MolBind: Multimodal Alignment of Language, Molecules, and Proteins.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules MolBind: Multimodal Alignment of Language, Molecules, and Proteins

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:20:38.426679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 376aa475-115c-4537-a96b-84334b62ccc9 · outbound

This paper cites A general offline reinforcement learning framework for interactive recommendation,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules A general offline reinforcement learning framework for interactive recommendation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.556814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 230e6aa8-6e55-4a98-b0a9-948430efffcd · outbound

This paper cites Cal-dpo: Calibrated direct preference optimization for language model alignment,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Cal-dpo: Calibrated direct preference optimization for language model alignment,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.543734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8ea738db-9b47-4566-a4e9-8d4bce48dedd · outbound

This paper cites Simple and asymmetric graph contrastive learning without augmen- tations,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Simple and asymmetric graph contrastive learning without augmen- tations,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.530877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0f67027f-6828-4c67-93f7-8712a2df2a9f · outbound

This paper cites Efficient contrastive learn- ing for fast and accurate inference on graphs,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Efficient contrastive learn- ing for fast and accurate inference on graphs,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.517891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 17a65cf0-57fb-4f28-9e49-345730922ea8 · outbound

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

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Geodiff: A geometric diffusion model for molecular conformation generation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.506321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8284d071-b514-44ef-9663-f460708f60b8 · outbound

This paper cites Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T19:20:38.346576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03533760-c942-46fd-9cdf-c6791b9b49a0 · outbound

This paper cites A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human profession- als,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human profession- als,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.495267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 67eedcde-b8c4-4da6-baef-28501eaf6286 · outbound

This paper cites Uni-mol: A universal 3d molecular representation learning framework,.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules Uni-mol: A universal 3d molecular representation learning framework,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:20:38.483891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e12a326d-fe94-437e-abf8-dab246d1625b · outbound

This paper cites 3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation.

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules 3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:20:38.399007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation af7f81ac-e371-4399-8791-76768f8e8037 · inbound

CLIP-Guided Backdoor Defense through Entropy-Based Poisoned Dataset Separation cites this paper.

CLIP-Guided Backdoor Defense through Entropy-Based Poisoned Dataset Separation GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:39:33.561030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.