Paper Citation Record · LEDGER

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation

As of 19 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2412.10436.

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

pith.paper-citation-record.v1
2412.10436 v3

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:12:21.168311Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy22
unresolved9
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f01a4c5-6bc0-4bd3-ac8f-ab91d7cc3711 · outbound

This paper cites Federated Learning Based on Dynamic Regularization.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Federated Learning Based on Dynamic Regularization

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03a909b9-8031-488c-b52d-f829760b6686 · outbound

This paper cites Personalized federated learning with gaussian processes.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Personalized federated learning with gaussian processes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.482994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 59b94189-f6e1-4116-a2a6-2458694b60d4 · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation LEAF: A Benchmark for Federated Settings

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.074363Z

Source-reported events for the cited work

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Observation e32bf28c-2902-43c2-9560-4ccf93dad413 · outbound

This paper cites A Comprehensive Survey of Scene Graphs: Generation and Application.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation A Comprehensive Survey of Scene Graphs: Generation and Application

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.077450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e0b666b-a4d9-4760-87c2-b3ffa93c679a · outbound

This paper cites Learning of visual relations: The devil is in the tails, in: Proceedings of the IEEE/CVFInternationalConferenceonComputerVision,pp.15404– 15413.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Learning of visual relations: The devil is in the tails, in: Proceedings of the IEEE/CVFInternationalConferenceonComputerVision,pp.15404– 15413

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.474876Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 14dda640-7289-4445-9bd6-af42d9ebe837 · outbound

This paper cites Sharpness- awareminimizationforefficientlyimprovinggeneralization.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Sharpness- awareminimizationforefficientlyimprovinggeneralization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.464484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e466e65d-ee1c-4c17-a0ea-b7306e76f8cd · outbound

This paper cites Fast r-cnn, in: Proceedings of the IEEE interna- tional conference on computer vision, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Fast r-cnn, in: Proceedings of the IEEE interna- tional conference on computer vision, pp

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.454733Z

Source-reported events for the cited work

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Observation e946dbd1-2a71-4ec4-bb8a-2888559315ff · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 8

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Source-reported events for the cited work

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Observation 04450c60-e347-48bd-afae-5dfb3d77015e · outbound

This paper cites Local pseudo-attributes for long-tailed recognition.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Local pseudo-attributes for long-tailed recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.444306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ee4b1853-28ed-49e4-ab84-fa50262c87b1 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Adam: A Method for Stochastic Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.097135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ffce1ef-71e1-4214-a5d3-3a948e606ca1 · outbound

This paper cites Panop- tic segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Panop- tic segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.434846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 21435b14-eff0-4e55-b18a-db642470b80a · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense imageannotations.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Visual genome: Connecting language and vision using crowdsourced dense imageannotations

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.425322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e9a964b8-6975-4132-bd6f-d3265f9ea3a7 · outbound

This paper cites Cifar-10 (canadian institute for advanced research).

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Cifar-10 (canadian institute for advanced research)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.416057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 26be561f-1586-4e96-b3aa-80d350ee2151 · outbound

This paper cites Rethinking the flat minima searching in federated learning, in: Forty-first International Conference on Ma- chine Learning.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Rethinking the flat minima searching in federated learning, in: Forty-first International Conference on Ma- chine Learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.405906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06e71d15-c315-4fcb-8e03-73a3b2890e1f · outbound

This paper cites Deeprelationalself-attentionnetworks forscenegraphgeneration.PatternRecognitionLetters153,200–206.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Deeprelationalself-attentionnetworks forscenegraphgeneration.PatternRecognitionLetters153,200–206

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.395358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68c91499-44b8-46aa-b062-74f294998329 · outbound

This paper cites On the Convergence of FedAvg on Non-IID Data.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation On the Convergence of FedAvg on Non-IID Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.116640Z

Source-reported events for the cited work

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Observation fbb2cae5-8290-4af7-9211-7d3fc2ded207 · outbound

This paper cites Uncertainty-aware scene graph generation.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Uncertainty-aware scene graph generation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.384374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6180b992-5878-4804-aa54-75101f1fb2dc · outbound

This paper cites Metavers:Meta-learnedversatile representations for personalized federated learning, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Metavers:Meta-learnedversatile representations for personalized federated learning, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.374235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 03d98340-5c1d-4b6f-abd6-53b66b1e64be · outbound

This paper cites Microsoft coco: Common objects in context, in: Computer Vision–ECCV 2014: 13th European Confer- ence, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, Springer.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Microsoft coco: Common objects in context, in: Computer Vision–ECCV 2014: 13th European Confer- ence, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, Springer

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.364984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 94c7e0f4-6761-466f-9bfe-8d09c44c0d43 · outbound

This paper cites Gps-net: Graph property sensing network for scene graph generation, in: Proceedings of the IEEE/CVFConferenceonComputerVisionandPatternRecognition, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Gps-net: Graph property sensing network for scene graph generation, in: Proceedings of the IEEE/CVFConferenceonComputerVisionandPatternRecognition, pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.355678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b0cdb288-3cc8-4a64-a54e-da1f25c8151b · outbound

This paper cites Pattern Recognition Letters 145, 187–193.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Pattern Recognition Letters 145, 187–193

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.346502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e428919b-d7fd-4e27-85f5-376eb24f23e8 · outbound

This paper cites Personalized federated learning on long-tailed data via knowledge distillation and generated features.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Personalized federated learning on long-tailed data via knowledge distillation and generated features

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.337743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a2f2b5a6-382c-4a2f-a667-0296b6ab4014 · outbound

This paper cites an unresolved cited work.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Unresolved cited work

Reference 23

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Source-reported events for the cited work

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Observation 28aca75c-b2e6-48d0-84a6-44026c5b763d · outbound

This paper cites Adaptive Federated Optimization.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Adaptive Federated Optimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.142309Z

Source-reported events for the cited work

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Observation b49897b3-8ad2-4856-8493-dc36a8e708d6 · outbound

This paper cites Federated learning with l1 regularization.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Federated learning with l1 regularization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.317215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7cf1258b-c994-43f4-b6f3-146db7285a52 · outbound

This paper cites Learning to compose dynamic tree structures for visual contexts, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Learning to compose dynamic tree structures for visual contexts, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition, pp

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.307258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76ff199b-70c0-4b56-827b-44cd81eaf319 · outbound

This paper cites 5410–5419.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation 5410–5419

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.297310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 31de53aa-8336-47be-bdde-d129927ce8a7 · outbound

This paper cites Panoptic scene graph generation, in: European Conference on Com- puter Vision, Springer.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Panoptic scene graph generation, in: European Conference on Com- puter Vision, Springer

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.286402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e206f792-036b-4e15-9692-0258d10a5f54 · outbound

This paper cites Neural motifs: Scenegraphparsingwithglobalcontext,in:ProceedingsoftheIEEE conference on computer vision and pattern recognition, pp.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Neural motifs: Scenegraphparsingwithglobalcontext,in:ProceedingsoftheIEEE conference on computer vision and pattern recognition, pp

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.277412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f8b4270-8b24-4eb5-b1b4-e8ca2c9173c7 · outbound

This paper cites Panoptic segmentation-based semantic embedding matching model for scene graph generation.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Panoptic segmentation-based semantic embedding matching model for scene graph generation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:12:21.268207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f8b92ae9-8504-442d-b389-aaeb31ef4f4e · outbound

This paper cites sky" or “grass.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation sky" or “grass

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T18:12:21.259751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad07de1a-4712-493f-8375-37b5a0467747 · outbound

This paper cites Prior research mentioned that the key point of GPS-Net explicitly models the direction of predicates, which is why it does not perform well on PSG dataset.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation Prior research mentioned that the key point of GPS-Net explicitly models the direction of predicates, which is why it does not perform well on PSG dataset

Reference 33

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T18:12:21.251046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d0f01d59-acb0-4109-ba1f-e31db1ede5a8 · outbound

This paper cites 1273–1282.

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation 1273–1282

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T18:12:21.139394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.