Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:32:21.896732Z
Paper Citation Record · LEDGER
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models
As of 20 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2412.15496.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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
Reference resolution
48 of 48 outbound references displayed
- verified exact1
- verified fuzzy27
- unresolved19
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation efedb952-f54c-41c1-91e7-89dc84bffc8c · outbound
This paper cites Community detection and stochastic block models: recent developments.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Community detection and stochastic block models: recent developments
Reference 1
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dc7d7823-020d-4598-a2f4-025bf0ca9915 · outbound
This paper cites and Sandon, C.
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.930547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6fb5a7eb-f951-4609-86bb-550e4f8f093f · outbound
This paper cites S., and Hall, G.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models S., and Hall, G
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.910191Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c0a40dcc-ea75-49a3-b7b0-c61863cd9c48 · outbound
This paper cites Almost Surely Asymptotically Constant Graph Neural Networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Almost Surely Asymptotically Constant Graph Neural Networks
Reference 4
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-11T11:32:22.193564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1cf51039-9328-47ea-95e7-117bcbe99bb8 · outbound
This paper cites Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.893565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1b458fc9-63d7-442d-a639-d3cd35130836 · outbound
This paper cites Effects of graph convolutions in multi-layer networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Effects of graph convolutions in multi-layer networks
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.876542Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3e99a336-5458-43a3-a66d-3c31b977bcfb · outbound
This paper cites An iterative clustering algorithm for the contextual stochastic block model with optimality guarantees.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models An iterative clustering algorithm for the contextual stochastic block model with optimality guarantees
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.858100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 14bb32cd-9601-4a98-8b97-a8a2d192368f · outbound
This paper cites Supervised community detection with line graph neural networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Supervised community detection with line graph neural networks
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.837394Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2eb6d217-8219-4e2d-8c6c-1ed15e817109 · outbound
This paper cites Contextual stochastic block models.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Contextual stochastic block models
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.819388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8bb4b8af-02b7-4edf-a1f8-b74d0f2c6cbd · outbound
This paper cites Exact recovery and bregman hard clustering of node-attributed stochastic block model.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Exact recovery and bregman hard clustering of node-attributed stochastic block model
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.800929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 987c0809-d1d7-4702-a102-d55b54f29beb · outbound
This paper cites and Zdeborova, L.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models and Zdeborova, L
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.781309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0887373c-f15f-4bb1-8fde-3152f6b0700a · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.763689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 749962b2-269c-4693-80fb-a0d02a62679f · outbound
This paper cites Graph neural networks for social recommendation.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph neural networks for social recommendation
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.656172Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7260532f-1334-43bb-83d3-6ace382af5e2 · outbound
This paper cites and Lenssen, J.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models and Lenssen, J
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.735288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a522dfa1-f674-4bc9-9fd9-a75071d14e42 · outbound
This paper cites Graph attention retrospective.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph attention retrospective
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.717692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation abb0e452-1032-4bab-9d1c-9611e7858a29 · outbound
This paper cites and Karo \'n ski, M.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models and Karo \'n ski, M
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.700769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7abc0bbc-e401-40d7-9274-2e36692ee38a · outbound
This paper cites D., Kosciolek, T., Leman, J.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models D., Kosciolek, T., Leman, J
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.682393Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b11cdb59-efe2-4dfb-8e73-9639bae5e6dc · outbound
This paper cites W., Laskey, K.
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.689072Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bbd9c0e7-e67d-43f3-af7e-473951b84c70 · outbound
This paper cites Open graph benchmark: Datasets for machine learning on graphs.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Open graph benchmark: Datasets for machine learning on graphs
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.659799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e60601d7-a418-45e9-9746-0cd6f83cd5fe · outbound
This paper cites S., Levi, A., and Valera, I.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models S., Levi, A., and Valera, I
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.642676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 42d0db76-7a09-45fa-af49-035ad9a59947 · outbound
This paper cites Not too little, not too much: a theoretical analysis of graph (over) smoothing.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Not too little, not too much: a theoretical analysis of graph (over) smoothing
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.625541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e089a247-1b0d-4f1b-819b-568e272c1dff · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 22
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.604700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1604990b-7f78-4b5e-94ef-13c7e4b150fe · outbound
This paper cites B., Rossi, R.
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.586384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 75fc0671-30bf-4a48-9bb3-a43de8787cbc · outbound
This paper cites E., Rivest, R.
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.566573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3f0789b8-6a37-403b-bda3-32cc5f2eb70e · outbound
This paper cites Towards deeper graph neural networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Towards deeper graph neural networks
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.545683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation de7bf6ca-b748-4a79-83e1-66147b196175 · outbound
This paper cites and Sen, S.
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.525264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 16d14a71-b7a0-49d0-aeb9-ec00f867fd6f · outbound
This paper cites When do graph neural networks help with node classification? investigating the homophily principle on node distinguishability.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models When do graph neural networks help with node classification? investigating the homophily principle on node distinguishability
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.502966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a9486c11-eda5-49d4-a089-1680e864a2eb · outbound
This paper cites Hyperspectral image classification using feature fusion hypergraph convolution neural network.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Hyperspectral image classification using feature fusion hypergraph convolution neural network
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.757383Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81ea639e-792f-4610-805e-ce0a5c806855 · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.484418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 58eee9be-b24b-408e-91a6-c65944836e11 · outbound
This paper cites A Survey on Oversmoothing in Graph Neural Networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models A Survey on Oversmoothing in Graph Neural Networks
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.772614Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4e3e5dd-6fd0-405f-99aa-8bb3bb4bf593 · outbound
This paper cites Graph attention networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph attention networks
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.782796Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e611079-8924-4eec-a221-22392ac5d235 · outbound
This paper cites Understanding heterophily for graph neural networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Understanding heterophily for graph neural networks
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.788194Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ea0c2b1-e305-47f5-9cbb-e35c6349e6be · outbound
This paper cites Graph attention convolution for point cloud semantic segmentation.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph attention convolution for point cloud semantic segmentation
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.436910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2ea15010-a720-4a63-890d-ec5b0379418f · outbound
This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.804721Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8300f00-a2f1-40f4-a70e-0c8f82e73fba · outbound
This paper cites Kgat: Knowledge graph attention network for recommendation.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Kgat: Knowledge graph attention network for recommendation
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.414318Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b8235562-14d0-4574-8493-da80cb9cfc42 · outbound
This paper cites R., and Li, P.
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.393357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9f237d5d-4976-4102-a1f2-b14ecc2c67cc · outbound
This paper cites Graph neural networks in recommender systems: a survey.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Graph neural networks in recommender systems: a survey
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.372448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 64f069ac-100f-4c22-8437-ac065944a69f · outbound
This paper cites A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.829688Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19bd5e62-4b0f-44be-beef-c72101f64f05 · outbound
This paper cites Demystifying oversmoothing in attention-based graph neural networks.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Demystifying oversmoothing in attention-based graph neural networks
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.350709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 565ac76a-787f-4910-8d73-270111423887 · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 40
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.331499Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2fd76e25-0558-47b2-a036-7fc2a3d4558a · outbound
This paper cites How powerful are graph neural networks? In International Conference on Learning Representations, 2018.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models How powerful are graph neural networks? In International Conference on Learning Representations, 2018
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.848506Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a0cdfc1-01f8-4eb4-bf56-69a6c042b54d · outbound
This paper cites Revisiting Over-smoothing in Deep GCNs.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Revisiting Over-smoothing in Deep GCNs
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.855510Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb28ac96-dd0c-4c1d-9e97-01d133b1635d · outbound
This paper cites You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T11:32:21.959782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 891d3094-0e4b-430f-83f5-343ef2385998 · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 44
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.299140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation be66a49c-dc5b-4727-9e81-854574125d99 · outbound
This paper cites an unresolved cited work.
Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models Unresolved cited work
Reference 45
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T11:32:22.272261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9bd91d3b-82e2-41ea-9d20-9de673628560 · outbound
This paper cites and Tan, V.
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.251613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cc23a366-87a1-4939-882f-468bf52b32c5 · outbound
This paper cites and Akoglu, L.
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:32:22.230853Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 13760481-c44b-4d55-996c-eab131b77628 · outbound
This paper cites write newline.
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:21.896732Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.