Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:01:48.988765Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:01:48.988765Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
64 of 64 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ba744979-b4b6-44b7-8bb4-f9f603a08cc6 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment T., Estrada, J
Reference 1
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Observation c97ef480-2598-48f0-80c9-f0e146c88b4b · outbound
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
Learning Chemical Reaction Representation with Reactant-Product Alignment Layer Normalization
Reference 3
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Observation 3f35bbe9-e331-40f8-9e22-71eddf5128b8 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Uncertainty-aware yield prediction with multimodal molecular features
Reference 4
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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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Learning Chemical Reaction Representation with Reactant-Product Alignment and Guestrin, C
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Learning Chemical Reaction Representation with Reactant-Product Alignment S., Babu, C
Reference 7
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Learning Chemical Reaction Representation with Reactant-Product Alignment BERT: pre-training of deep bidirectional transformers for language understanding
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Learning Chemical Reaction Representation with Reactant-Product Alignment and Lenssen, J
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Learning Chemical Reaction Representation with Reactant-Product Alignment Description of organic reactions based on imaginary transition structures
Reference 10
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Observation 089ca015-cce8-4950-a5f6-397f68bba2ad · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment J., Coley, C
Reference 11
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Observation 98fbfcbe-f278-43b9-8b47-16c040a241ee · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Computer software review: Reaxys, 2009
Reference 12
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Observation de06ba18-462a-47eb-a75d-42cb4046297f · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment W., Wu, H., Ranasinghe, D., Heid, E., Struble, T
Reference 13
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Observation d3f046f1-013a-431e-bcdf-12ac30b4e77f · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Improving chemical reaction yield prediction using pre-trained graph neural networks
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Learning Chemical Reaction Representation with Reactant-Product Alignment and Oprea, T
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Observation 75b62fa3-460c-4e3e-a500-de43805454e9 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment P., Chung, Y., Li, S.-C., Graff, D
Reference 16
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Observation 8cbcefea-34df-47c2-8ff0-d2c99e4b6cf6 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Open graph benchmark: Datasets for machine learning on graphs
Reference 17
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Observation f21b934c-b1cb-47ca-833c-fe56cafe7203 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Strategies for pre-training graph neural networks
Reference 18
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Observation b2683d90-e4d4-4581-ba80-0c7571b2cadc · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work
Reference 19
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Observation 2e1f3c11-4639-4f1d-abea-21eb3139a38d · outbound
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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Observation fd548d37-ca68-460e-92f4-f675465721ed · outbound
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
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Observation 42c67ccf-e94d-436b-8b7d-ff84840ee3ed · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Predicting organic reaction outcomes with weisfeiler-lehman network
Reference 22
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Observation 39ce8929-d105-4ce1-b150-a313a31df573 · outbound
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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Observation ba2b3dcb-c82a-420e-a446-ee63de1dc65a · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment M., Maser, M
Reference 24
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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
Learning Chemical Reaction Representation with Reactant-Product Alignment A., Thiessen, P
Reference 26
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Observation 519af209-01db-4c3a-adb4-490de76d9dba · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Adam: A Method for Stochastic Optimization
Reference 27
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Observation 5041dc2a-add2-4817-9db4-a820217d59cc · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Uncertainty-aware prediction of chemical reaction yields with graph neural networks
Reference 28
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Observation 09916c11-e735-438a-975c-347b7aff1666 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work
Reference 29
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Observation c2ca7d9f-5874-4850-bad6-638757dd53c7 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Reaction performance prediction with an extrapolative and interpretable graph model based on chemical knowledge
Reference 30
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Learning Chemical Reaction Representation with Reactant-Product Alignment Predicting regioselectivity in radical c- h functionalization of heterocycles through machine learning
Reference 31
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Observation dedc9a86-83e7-415c-b6b0-deb1cca9b1f6 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment and Zhang, Y
Reference 32
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Observation 20eb242d-2f88-4873-aab8-4c47b3edd685 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment The development of pharmacophore modeling: Generation and recent applications in drug discovery
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Learning Chemical Reaction Representation with Reactant-Product Alignment R., Cui, A
Reference 34
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Learning Chemical Reaction Representation with Reactant-Product Alignment Pistachio: Search and faceting of large reaction databases
Reference 35
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Observation 4a9eaf2b-37d8-4acb-9202-6c841e30a8d6 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work
Reference 36
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Observation cb7d5517-ff09-46d7-a39a-b343570977e4 · outbound
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
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Observation 3c5f082a-ca49-4b4b-bcd1-ffc8af250f01 · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Emerging computational approaches for the study of regio-and stereoselectivity in organic synthesis
Reference 38
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Learning Chemical Reaction Representation with Reactant-Product Alignment Recent developments in the reduction of aromatic and aliphatic nitro compounds to amines
Reference 39
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Observation 859016b5-81d2-46f2-ad64-e1d393f0d08b · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Pytorch: An imperative style, high-performance deep learning library
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Learning Chemical Reaction Representation with Reactant-Product Alignment Reaction classification and yield prediction using the differential reaction fingerprint drfp
Reference 41
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Learning Chemical Reaction Representation with Reactant-Product Alignment Molecule edit graph attention network: modeling chemical reactions as sequences of graph edits
Reference 42
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Learning Chemical Reaction Representation with Reactant-Product Alignment A structure-based platform for predicting chemical reactivity
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Learning Chemical Reaction Representation with Reactant-Product Alignment A., Bekas, C., and Lee, A
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Learning Chemical Reaction Representation with Reactant-Product Alignment Extraction of organic chemistry grammar from unsupervised learning of chemical reactions
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Learning Chemical Reaction Representation with Reactant-Product Alignment C., Nair, V
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Learning Chemical Reaction Representation with Reactant-Product Alignment Unresolved cited work
Reference 48
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Learning Chemical Reaction Representation with Reactant-Product Alignment Catalytic Transfer Hydrogenation of Nitronarenes under Mild Conditions
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Learning Chemical Reaction Representation with Reactant-Product Alignment N., Kaiser, ., and Polosukhin, I
Reference 51
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Learning Chemical Reaction Representation with Reactant-Product Alignment Graph attention networks
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Learning Chemical Reaction Representation with Reactant-Product Alignment Retroformer: Pushing the limits of end-to-end retrosynthesis transformer
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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
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Learning Chemical Reaction Representation with Reactant-Product Alignment Smiles, a chemical language and information system
Reference 55
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Learning Chemical Reaction Representation with Reactant-Product Alignment Retroxpert: Decompose retrosynthesis prediction like a chemist
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Reference 57
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Learning Chemical Reaction Representation with Reactant-Product Alignment and Zhang, R
Reference 58
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Learning Chemical Reaction Representation with Reactant-Product Alignment Z., Zhao, Y., Xu, H., Kuramshin, A., et al
Reference 59
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Learning Chemical Reaction Representation with Reactant-Product Alignment F., Henle, J
Reference 60
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Learning Chemical Reaction Representation with Reactant-Product Alignment Ualign: pushing the limit of template-free retrosynthesis prediction with unsupervised smiles alignment
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Observation 8c967954-ec08-41b9-b2f1-0996e8fb780a · outbound
Learning Chemical Reaction Representation with Reactant-Product Alignment Adding conditional control to text-to-image diffusion models
Reference 62
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Learning Chemical Reaction Representation with Reactant-Product Alignment Uni-mol: A universal 3d molecular representation learning framework
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Learning Chemical Reaction Representation with Reactant-Product Alignment write newline
Reference 64
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No inbound Pith citation observations are available.