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Paper Citation Record · LEDGER

Learning Chemical Reaction Representation with Reactant-Product Alignment

As of 13 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2411.17629.

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

pith.paper-citation-record.v1
2411.17629 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:01:48.988765Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

64 of 64 outbound references displayed

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  • unresolved20
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba744979-b4b6-44b7-8bb4-f9f603a08cc6 · outbound

This paper cites T., Estrada, J.

Learning Chemical Reaction Representation with Reactant-Product Alignment T., Estrada, J

Reference 1

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Observation c97ef480-2598-48f0-80c9-f0e146c88b4b · outbound

This paper cites Reagent prediction with a molecular transformer improves reaction data quality.

Learning Chemical Reaction Representation with Reactant-Product Alignment Reagent prediction with a molecular transformer improves reaction data quality

Reference 2

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Observation 422db8d4-0863-4c0e-be4a-1ec39bd9e89b · outbound

This paper cites Layer Normalization.

Learning Chemical Reaction Representation with Reactant-Product Alignment Layer Normalization

Reference 3

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Source-reported events for the cited work

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Observation 3f35bbe9-e331-40f8-9e22-71eddf5128b8 · outbound

This paper cites Uncertainty-aware yield prediction with multimodal molecular features.

Learning Chemical Reaction Representation with Reactant-Product Alignment Uncertainty-aware yield prediction with multimodal molecular features

Reference 4

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Observation 2cb6f6b6-86fc-4709-94c9-ff5c892700e1 · outbound

This paper cites Precise atom-to-atom mapping for organic reactions via human-in-the-loop machine learning.

Learning Chemical Reaction Representation with Reactant-Product Alignment Precise atom-to-atom mapping for organic reactions via human-in-the-loop machine learning

Reference 5

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Source-reported events for the cited work

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Observation 002e04d9-198b-4b59-8ab1-dbce11a9d286 · outbound

This paper cites and Guestrin, C.

Learning Chemical Reaction Representation with Reactant-Product Alignment and Guestrin, C

Reference 6

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Source-reported events for the cited work

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Observation 23b2c2d2-472a-44d1-ad88-e70daada1a3d · outbound

This paper cites S., Babu, C.

Learning Chemical Reaction Representation with Reactant-Product Alignment S., Babu, C

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5835b7c5-5a5b-4a17-8ed9-8f9dd0f363fc · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding.

Learning Chemical Reaction Representation with Reactant-Product Alignment BERT: pre-training of deep bidirectional transformers for language understanding

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cb781940-26c6-4a18-b9cf-8843e7b482aa · outbound

This paper cites and Lenssen, J.

Learning Chemical Reaction Representation with Reactant-Product Alignment and Lenssen, J

Reference 9

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Observation 2082fed5-9f29-4b31-bad9-313c5ba72d26 · outbound

This paper cites Description of organic reactions based on imaginary transition structures.

Learning Chemical Reaction Representation with Reactant-Product Alignment Description of organic reactions based on imaginary transition structures

Reference 10

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Source-reported events for the cited work

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Observation 089ca015-cce8-4950-a5f6-397f68bba2ad · outbound

This paper cites J., Coley, C.

Learning Chemical Reaction Representation with Reactant-Product Alignment J., Coley, C

Reference 11

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Observation 98fbfcbe-f278-43b9-8b47-16c040a241ee · outbound

This paper cites Computer software review: Reaxys, 2009.

Learning Chemical Reaction Representation with Reactant-Product Alignment Computer software review: Reaxys, 2009

Reference 12

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Source-reported events for the cited work

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Observation de06ba18-462a-47eb-a75d-42cb4046297f · outbound

This paper cites W., Wu, H., Ranasinghe, D., Heid, E., Struble, T.

Learning Chemical Reaction Representation with Reactant-Product Alignment W., Wu, H., Ranasinghe, D., Heid, E., Struble, T

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation d3f046f1-013a-431e-bcdf-12ac30b4e77f · outbound

This paper cites Improving chemical reaction yield prediction using pre-trained graph neural networks.

Learning Chemical Reaction Representation with Reactant-Product Alignment Improving chemical reaction yield prediction using pre-trained graph neural networks

Reference 14

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Source-reported events for the cited work

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Observation 1dbe4c38-0f6f-49ec-906a-189df7764808 · outbound

This paper cites and Oprea, T.

Learning Chemical Reaction Representation with Reactant-Product Alignment and Oprea, T

Reference 15

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Source-reported events for the cited work

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Observation 75b62fa3-460c-4e3e-a500-de43805454e9 · outbound

This paper cites P., Chung, Y., Li, S.-C., Graff, D.

Learning Chemical Reaction Representation with Reactant-Product Alignment P., Chung, Y., Li, S.-C., Graff, D

Reference 16

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Source-reported events for the cited work

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Observation 8cbcefea-34df-47c2-8ff0-d2c99e4b6cf6 · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

Learning Chemical Reaction Representation with Reactant-Product Alignment Open graph benchmark: Datasets for machine learning on graphs

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f21b934c-b1cb-47ca-833c-fe56cafe7203 · outbound

This paper cites Strategies for pre-training graph neural networks.

Learning Chemical Reaction Representation with Reactant-Product Alignment Strategies for pre-training graph neural networks

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b2683d90-e4d4-4581-ba80-0c7571b2cadc · outbound

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Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work

Reference 19

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Source-reported events for the cited work

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Observation 2e1f3c11-4639-4f1d-abea-21eb3139a38d · outbound

This paper cites Graph neural networks with multiple feature extraction paths for chemical property estimation.

Learning Chemical Reaction Representation with Reactant-Product Alignment Graph neural networks with multiple feature extraction paths for chemical property estimation

Reference 20

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Source-reported events for the cited work

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Observation fd548d37-ca68-460e-92f4-f675465721ed · outbound

This paper cites Drugood: Out-of-distribution dataset curator and benchmark for ai-aided drug discovery--a focus on affinity prediction problems with noise annotations.

Learning Chemical Reaction Representation with Reactant-Product Alignment Drugood: Out-of-distribution dataset curator and benchmark for ai-aided drug discovery--a focus on affinity prediction problems with noise annotations

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 42c67ccf-e94d-436b-8b7d-ff84840ee3ed · outbound

This paper cites Predicting organic reaction outcomes with weisfeiler-lehman network.

Learning Chemical Reaction Representation with Reactant-Product Alignment Predicting organic reaction outcomes with weisfeiler-lehman network

Reference 22

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Source-reported events for the cited work

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Observation 39ce8929-d105-4ce1-b150-a313a31df573 · outbound

This paper cites A substructure-based screening approach to uncover n-nitrosamines in drug substances.

Learning Chemical Reaction Representation with Reactant-Product Alignment A substructure-based screening approach to uncover n-nitrosamines in drug substances

Reference 23

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Source-reported events for the cited work

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Observation ba2b3dcb-c82a-420e-a446-ee63de1dc65a · outbound

This paper cites M., Maser, M.

Learning Chemical Reaction Representation with Reactant-Product Alignment M., Maser, M

Reference 24

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Source-reported events for the cited work

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This paper cites W., Zhang, X., Krenske, E.

Learning Chemical Reaction Representation with Reactant-Product Alignment W., Zhang, X., Krenske, E

Reference 25

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Observation 9fc59fc9-1741-4e4b-9bf0-71fb54ff61d6 · outbound

This paper cites A., Thiessen, P.

Learning Chemical Reaction Representation with Reactant-Product Alignment A., Thiessen, P

Reference 26

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Observation 519af209-01db-4c3a-adb4-490de76d9dba · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Chemical Reaction Representation with Reactant-Product Alignment Adam: A Method for Stochastic Optimization

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Uncertainty-aware prediction of chemical reaction yields with graph neural networks.

Learning Chemical Reaction Representation with Reactant-Product Alignment Uncertainty-aware prediction of chemical reaction yields with graph neural networks

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work

Reference 29

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This paper cites Reaction performance prediction with an extrapolative and interpretable graph model based on chemical knowledge.

Learning Chemical Reaction Representation with Reactant-Product Alignment Reaction performance prediction with an extrapolative and interpretable graph model based on chemical knowledge

Reference 30

Resolution
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Source-reported events for the cited work

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This paper cites Predicting regioselectivity in radical c- h functionalization of heterocycles through machine learning.

Learning Chemical Reaction Representation with Reactant-Product Alignment Predicting regioselectivity in radical c- h functionalization of heterocycles through machine learning

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation dedc9a86-83e7-415c-b6b0-deb1cca9b1f6 · outbound

This paper cites and Zhang, Y.

Learning Chemical Reaction Representation with Reactant-Product Alignment and Zhang, Y

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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This paper cites The development of pharmacophore modeling: Generation and recent applications in drug discovery.

Learning Chemical Reaction Representation with Reactant-Product Alignment The development of pharmacophore modeling: Generation and recent applications in drug discovery

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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This paper cites R., Cui, A.

Learning Chemical Reaction Representation with Reactant-Product Alignment R., Cui, A

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Learning Chemical Reaction Representation with Reactant-Product Alignment Pistachio: Search and faceting of large reaction databases

Reference 35

Resolution
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Observation 4a9eaf2b-37d8-4acb-9202-6c841e30a8d6 · outbound

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Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work

Reference 36

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Observation cb7d5517-ff09-46d7-a39a-b343570977e4 · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

Learning Chemical Reaction Representation with Reactant-Product Alignment T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 37

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3c5f082a-ca49-4b4b-bcd1-ffc8af250f01 · outbound

This paper cites Emerging computational approaches for the study of regio-and stereoselectivity in organic synthesis.

Learning Chemical Reaction Representation with Reactant-Product Alignment Emerging computational approaches for the study of regio-and stereoselectivity in organic synthesis

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.402055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.887797Z digest=sha256:dc62e7e881c24b0e4895998dd79767680a6825416c5c92f5c051d9e7996dbb2f

Observation a2a98653-2f74-4295-93fe-4cd96cf3dd9b · outbound

This paper cites Recent developments in the reduction of aromatic and aliphatic nitro compounds to amines.

Learning Chemical Reaction Representation with Reactant-Product Alignment Recent developments in the reduction of aromatic and aliphatic nitro compounds to amines

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.387784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.891820Z digest=sha256:55cc787ff23ff58cdf731655bb9b657806b05f013856006c760e2706305f9ca4

Observation 859016b5-81d2-46f2-ad64-e1d393f0d08b · outbound

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

Learning Chemical Reaction Representation with Reactant-Product Alignment Pytorch: An imperative style, high-performance deep learning library

Reference 40

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unresolved
no resolver link, observed 2026-08-12T12:01:48.895945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.895945Z digest=sha256:0f923c7082fb108c33d69e3242a6857dc795c9bd0386f460e319218f6fa7c991

Observation c370290c-db6d-488e-acf8-24b880582c29 · outbound

This paper cites Reaction classification and yield prediction using the differential reaction fingerprint drfp.

Learning Chemical Reaction Representation with Reactant-Product Alignment Reaction classification and yield prediction using the differential reaction fingerprint drfp

Reference 41

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.899776Z digest=sha256:418a7b773da0172799032108d2b0c6541f374b831b8e2fcda06dc072fa4fed0d

Observation b8ff52ed-3340-401c-8269-6632db75b20a · outbound

This paper cites Molecule edit graph attention network: modeling chemical reactions as sequences of graph edits.

Learning Chemical Reaction Representation with Reactant-Product Alignment Molecule edit graph attention network: modeling chemical reactions as sequences of graph edits

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.354916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.903591Z digest=sha256:63483bc3b1a4a24008b96f3b20e6d9ee68b334b655e09ff125bb42de6e7cfcc0

Observation ff6a0ce3-572c-4412-af41-a4f6827e7c32 · outbound

This paper cites A structure-based platform for predicting chemical reactivity.

Learning Chemical Reaction Representation with Reactant-Product Alignment A structure-based platform for predicting chemical reactivity

Reference 43

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.907413Z digest=sha256:4d9e76e6ae5e58d1a0117ed4d973650b68fdf0d519f26ffe2a3012bad6ffb371

Observation 34868682-12e6-4f37-87cf-43461aa41c30 · outbound

This paper cites A., Bekas, C., and Lee, A.

Learning Chemical Reaction Representation with Reactant-Product Alignment A., Bekas, C., and Lee, A

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.342176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.911220Z digest=sha256:745992f2f10a819a15831d742687670d96aff6c958b8864d23cdde4163156c36

Observation d94fb77a-5f2b-46e4-9bde-1fbdac9d19e6 · outbound

This paper cites Extraction of organic chemistry grammar from unsupervised learning of chemical reactions.

Learning Chemical Reaction Representation with Reactant-Product Alignment Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.914858Z digest=sha256:5c7dae7c41cb1f1b338d845912f68165256e868f9c26f59a74c7ad11f882b811

Observation f0fd123b-6ab0-4cc3-b7ba-29e40ff1f1aa · outbound

This paper cites C., Nair, V.

Learning Chemical Reaction Representation with Reactant-Product Alignment C., Nair, V

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.316266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.918654Z digest=sha256:747e6cf672b3690c80dbb7772aaa5bce9436e584b9d4027b8bba0cbf407e9693

Observation aad5a088-da90-475e-a4e1-45d95c397069 · outbound

This paper cites C., Laino, T., and Reymond, J.-L.

Learning Chemical Reaction Representation with Reactant-Product Alignment C., Laino, T., and Reymond, J.-L

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.303582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.922503Z digest=sha256:d5dc54f58157b75636dc945640f01a007bfd78dbb905c94411f0541c386c879f

Observation 5290ea66-52f8-43b4-81a6-a289e2b33a0f · outbound

This paper cites an unresolved cited work.

Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:01:49.292076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.926388Z digest=sha256:c9789884c7ad76bb573e748ece0144ee1a72736ed005211392af8b87530a9345

Observation c2f67142-6201-464e-8ba0-4eea38394ba8 · outbound

This paper cites Catalytic Transfer Hydrogenation of Nitronarenes under Mild Conditions.

Learning Chemical Reaction Representation with Reactant-Product Alignment Catalytic Transfer Hydrogenation of Nitronarenes under Mild Conditions

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.280592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.930284Z digest=sha256:d44b3c2d2e03f7de9280d64f0e63f963f14ed7e6f66cc9a1cb6e4a39da281868

Observation dbc44fbc-bd20-48ed-8c41-751973647b01 · outbound

This paper cites Prediction of chemical reaction yields with large-scale multi-view pre-training.

Learning Chemical Reaction Representation with Reactant-Product Alignment Prediction of chemical reaction yields with large-scale multi-view pre-training

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.268808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.934379Z digest=sha256:0ccc85311f6cb3adba0a29b5c502c47b1727e2131f090f38a7e55fac9c6f2f46

Observation d7d1f89a-e116-47ab-b971-f87a5d87114e · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Learning Chemical Reaction Representation with Reactant-Product Alignment N., Kaiser, ., and Polosukhin, I

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.939196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.939196Z digest=sha256:7b3e03cb3a8713c530795186c112420c48aa53e4e28c1304256a5558528ae35d

Observation 72288342-3b28-43a0-9c8a-abe070d8e862 · outbound

This paper cites Graph attention networks.

Learning Chemical Reaction Representation with Reactant-Product Alignment Graph attention networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.943704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.943704Z digest=sha256:310b5be29c597e35056ff67ef892e247a499a0fb4d1a4f17b45805f4ce58c0eb

Observation c4c5d300-9539-4927-83f5-e5030c5fc135 · outbound

This paper cites Retroformer: Pushing the limits of end-to-end retrosynthesis transformer.

Learning Chemical Reaction Representation with Reactant-Product Alignment Retroformer: Pushing the limits of end-to-end retrosynthesis transformer

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.238537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.947599Z digest=sha256:d0c4d6616ebfdc75db461b16d67d60f42044cb68661d5e86bd602d1d545fee08

Observation 16349cf4-722a-4abb-9efa-6ec3677cae6a · outbound

This paper cites Generic interpretable reaction condition predictions with open reaction condition datasets and unsupervised learning of reaction center.

Learning Chemical Reaction Representation with Reactant-Product Alignment Generic interpretable reaction condition predictions with open reaction condition datasets and unsupervised learning of reaction center

Reference 54

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.951412Z digest=sha256:c8b747a4e51d2963ad0d69de6ef0e779ade0623b82eef427ed8d31b67023b45d

Observation 9f04fa75-eb81-4e77-a953-5526168ac17f · outbound

This paper cites Smiles, a chemical language and information system.

Learning Chemical Reaction Representation with Reactant-Product Alignment Smiles, a chemical language and information system

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.955484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.955484Z digest=sha256:7eb64a2c687236b2db51c807eaab67da5e85574cfe86fbd0106a31929bf0e9c5

Observation 92e7efa1-1ee8-42b9-b2ca-50d6803f774a · outbound

This paper cites Retroxpert: Decompose retrosynthesis prediction like a chemist.

Learning Chemical Reaction Representation with Reactant-Product Alignment Retroxpert: Decompose retrosynthesis prediction like a chemist

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.218308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.959280Z digest=sha256:fd34aca2d6793bcdf7c116f5e54bfcb240f7057ba7f6ada7e2634a319a916fe9

Observation 7a4a5d7a-10e2-4cfa-b0bf-bda3c27301f5 · outbound

This paper cites Learning substructure invariance for out-of-distribution molecular representations.

Learning Chemical Reaction Representation with Reactant-Product Alignment Learning substructure invariance for out-of-distribution molecular representations

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.205757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.962926Z digest=sha256:d751fdea4a4071f82ecb52f505d0e503fb1f61d8c53c545edc6a7ff3217c6b66

Observation 52b33bca-f4ea-4788-9bb3-1d443fe6848a · outbound

This paper cites and Zhang, R.

Learning Chemical Reaction Representation with Reactant-Product Alignment and Zhang, R

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.194223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.966413Z digest=sha256:6311189e1baa8653fd4f55c5038f11bd2c9a8bf5dd3587647a7ed2b5f26f72ff

Observation b680d0be-6bc8-4e49-b767-05caf0a72a79 · outbound

This paper cites Z., Zhao, Y., Xu, H., Kuramshin, A., et al.

Learning Chemical Reaction Representation with Reactant-Product Alignment Z., Zhao, Y., Xu, H., Kuramshin, A., et al

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.181492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.969913Z digest=sha256:e8c22959ebe7cfc85d51958aa02b7b49472fe0e14b2956b82b78a8bc0c0f23fe

Observation c99286c9-e973-4173-88f4-84d73d29d973 · outbound

This paper cites F., Henle, J.

Learning Chemical Reaction Representation with Reactant-Product Alignment F., Henle, J

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.170145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.973691Z digest=sha256:d6aa0c073217ac119d0119b92677cc28b2c5efd5790a2ea942ab98384221661e

Observation 780a29ee-9c47-4c12-bd0e-1ad9e0143997 · outbound

This paper cites Ualign: pushing the limit of template-free retrosynthesis prediction with unsupervised smiles alignment.

Learning Chemical Reaction Representation with Reactant-Product Alignment Ualign: pushing the limit of template-free retrosynthesis prediction with unsupervised smiles alignment

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:01:49.158115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T12:01:48.977222Z digest=sha256:c261a437d9b14d5b8f015276e88828eee4461f744eb7833afdd1a8a4f0fe1b59

Observation 8c967954-ec08-41b9-b2f1-0996e8fb780a · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Learning Chemical Reaction Representation with Reactant-Product Alignment Adding conditional control to text-to-image diffusion models

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.980960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.980960Z digest=sha256:887cc909cd8a6a56b7d7a5f66c933a9560ddbd3e797d38619fad83b5132c4353

Observation be4cc595-02b3-4bf0-a2cd-cef888cb33db · outbound

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

Learning Chemical Reaction Representation with Reactant-Product Alignment Uni-mol: A universal 3d molecular representation learning framework

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.984682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.984682Z digest=sha256:3f4b09421a2cad4a453f0950bcc74179f9c64a79e3e996ffdb99fe4a62cc9367

Observation f8066b18-0aad-40d7-a144-aee6350b81f3 · outbound

This paper cites write newline.

Learning Chemical Reaction Representation with Reactant-Product Alignment write newline

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-12T12:01:48.988765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:01:48.988765Z digest=sha256:ccb98d98139fc206501f7eb18e7cabc742afd748ec15a0468a23e05c26670bcc

Pith citing papers

No inbound Pith citation observations are available.