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Paper Citation Record · LEDGER

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2508.07122.

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

pith.paper-citation-record.v1
2508.07122 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:22:00.015034Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved5
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d842dec-a30a-4496-8a6e-c3959a3c503f · outbound

This paper cites Micro frontend based performance improvement and prediction for microservices using machine learning,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Micro frontend based performance improvement and prediction for microservices using machine learning,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation db602012-94c2-43f2-8b69-06e01b8df0dd · outbound

This paper cites Suanming: Explainable prediction of performance degradations in microservice applications,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Suanming: Explainable prediction of performance degradations in microservice applications,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T22:22:00.324322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d281a0de-2ca9-46b0-85d2-6450378de4c7 · outbound

This paper cites Intelligent performance prediction: The use case of a Hadoop cluster,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Intelligent performance prediction: The use case of a Hadoop cluster,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4395a821-fc90-48b9-9d8b-d46b9cbec8a5 · outbound

This paper cites Leveraging convolutional neural network-transformer synergy for predictive modeling in risk- based applications,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Leveraging convolutional neural network-transformer synergy for predictive modeling in risk- based applications,

Reference 4

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raw_fallback, observed 2026-08-05T22:22:00.303209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation bec75f62-ed48-4fcb-9768-408f2b15af76 · outbound

This paper cites Market turbulence prediction and risk control with improved A3C reinforcement learning,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Market turbulence prediction and risk control with improved A3C reinforcement learning,

Reference 5

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raw_fallback, observed 2026-08-05T22:22:00.292801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a6882948-4dec-436a-8d07-a1fa9794b0d9 · outbound

This paper cites AI back-end as a service for learning switching of mobile apps between the fog and the cloud,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks AI back-end as a service for learning switching of mobile apps between the fog and the cloud,

Reference 6

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raw_fallback, observed 2026-08-05T22:22:00.282438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a9016979-3e72-454b-aa2e-45ce92e3197c · outbound

This paper cites Entity boundary detection in social texts using BiLSTM-CRF with integrated social features,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Entity boundary detection in social texts using BiLSTM-CRF with integrated social features,

Reference 7

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raw_fallback, observed 2026-08-05T22:22:00.272410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:21:59.942946Z digest=sha256:c9e337831218f5b121a191715298ac06d9e6db3bd2afc2a771fc86d8e9661fb4

Observation b9ad2bf2-9b11-4f58-a542-1a39171cd65d · outbound

This paper cites Unsupervised detection of fraudulent transactions in e-commerce using contrastive learning,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Unsupervised detection of fraudulent transactions in e-commerce using contrastive learning,

Reference 8

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raw_fallback, observed 2026-08-05T22:22:00.262408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:21:59.946053Z digest=sha256:98d1ba6f997a3a1f2c92ff1fa1b8bb2564b5dba324a6dc1079cc23460b196931

Observation dc5621a4-8bb5-475f-b7a3-66dc692676ee · outbound

This paper cites Regression analysis of predictions and forecasts of cloud data center KPIs using the boosted decision tree algorithm,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Regression analysis of predictions and forecasts of cloud data center KPIs using the boosted decision tree algorithm,

Reference 9

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raw_fallback, observed 2026-08-05T22:22:00.252752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 44963a66-b757-4a09-9e1f-fa658f18400b · outbound

This paper cites Microservice-oriented workload prediction using deep learning,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Microservice-oriented workload prediction using deep learning,

Reference 10

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raw_fallback, observed 2026-08-05T22:22:00.242345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2bfad34e-3fd0-438c-9699-8b976caf72e0 · outbound

This paper cites PERT-GNN: Latency prediction for microservice-based cloud-native applications via graph neural networks,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks PERT-GNN: Latency prediction for microservice-based cloud-native applications via graph neural networks,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8b3060c5-6fa0-4681-ba55-5b008764e5ac · outbound

This paper cites Cross-scale attention and multi- layer feature fusion YOLOv8 for skin disease target detection in medical images,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Cross-scale attention and multi- layer feature fusion YOLOv8 for skin disease target detection in medical images,

Reference 12

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raw_fallback, observed 2026-08-05T22:22:00.220839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 56997a35-ae98-4241-8b32-6b9ec32ac971 · outbound

This paper cites RT-DETR-based multimodal detection with modality attention and feature alignment,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks RT-DETR-based multimodal detection with modality attention and feature alignment,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-05T22:22:00.210316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0d67ce5f-a3e4-48f1-9927-09013c7ab1a8 · outbound

This paper cites Integrating system state into spatio temporal graph neural network for microservice workload prediction,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Integrating system state into spatio temporal graph neural network for microservice workload prediction,

Reference 14

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raw_fallback, observed 2026-08-05T22:22:00.199849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8799c0a7-b44d-4789-8067-7fac3b8837a1 · outbound

This paper cites A hybrid recommendation approach integrating matrix decomposition and deep neural networks for enhanced accuracy and generalization,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks A hybrid recommendation approach integrating matrix decomposition and deep neural networks for enhanced accuracy and generalization,

Reference 15

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raw_fallback, observed 2026-08-05T22:22:00.188531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 81c0bed4-88c8-4dda-87f6-228fb684117e · outbound

This paper cites Context-aware rule mining using a dynamic transformer- based framework,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Context-aware rule mining using a dynamic transformer- based framework,

Reference 16

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raw_fallback, observed 2026-08-05T22:22:00.178660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:21:59.971895Z digest=sha256:abff83fb484f3fcf4bf9ffc4fbddd80b0497caa2ecba6bda68c8414a5abc53d2

Observation 4f12ac02-f0bc-4acc-a872-16760b7b9714 · outbound

This paper cites Federated Learning for Cross-Domain Data Privacy: A Distributed Approach to Secure Collaboration.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Federated Learning for Cross-Domain Data Privacy: A Distributed Approach to Secure Collaboration

Reference 17

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e6f647c1-4ed1-4437-b4dd-d6e6216b42d6 · outbound

This paper cites Dynamic operating system scheduling using double DQN: A reinforcement learning approach to task optimization,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Dynamic operating system scheduling using double DQN: A reinforcement learning approach to task optimization,

Reference 18

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raw_fallback, observed 2026-08-05T22:22:00.168912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2431faa0-76f9-4bf3-b3a6-2a7d05f87397 · outbound

This paper cites Temporal-spatial deep learning for memory usage forecasting in cloud servers,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Temporal-spatial deep learning for memory usage forecasting in cloud servers,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-05T22:22:00.157999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a7049817-5341-4e78-a7cd-45e82d13f6f7 · outbound

This paper cites Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networks.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networks

Reference 20

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unresolved
no resolver link, observed 2026-08-05T22:21:59.984698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 339edf5c-1cc6-42df-a525-16b0bf1fd4b5 · outbound

This paper cites Knowledge-informed policy structuring for multi-agent collaboration using language models,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Knowledge-informed policy structuring for multi-agent collaboration using language models,

Reference 21

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raw_fallback, observed 2026-08-05T22:22:00.146962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 14c9103f-b148-4f72-a38b-26c518f643e8 · outbound

This paper cites Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks

Reference 22

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no resolver link, observed 2026-08-05T22:21:59.991084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:21:59.991084Z digest=sha256:05120b557892ea3204c028acd485b28843bd668f5d8ff6a824404cbdd1bc03a7

Observation e0d2704f-7b22-4049-b2b4-7d94398021a3 · outbound

This paper cites Time-Series Learning for Proactive Fault Prediction in Distributed Systems with Deep Neural Structures.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Time-Series Learning for Proactive Fault Prediction in Distributed Systems with Deep Neural Structures

Reference 23

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Unavailable: canonical work link unavailable.

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Observation d10d7e87-8c89-4f67-9b31-a1a2d7103c51 · outbound

This paper cites Self-supervised credit scoring with masked autoencoders: Addressing data gaps and noise robustly,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Self-supervised credit scoring with masked autoencoders: Addressing data gaps and noise robustly,

Reference 24

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raw_fallback, observed 2026-08-05T22:22:00.135568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:21:59.997868Z digest=sha256:af9528209407586e8e5c6eca983bf440e7227adb2bb59b3140cb6a00082118d3

Observation 0ef01a2d-b5a3-4a2d-8ca3-124d7277a088 · outbound

This paper cites Temporal graph representation learning for evolving user behavior in transactional networks,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Temporal graph representation learning for evolving user behavior in transactional networks,

Reference 25

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raw_fallback, observed 2026-08-05T22:22:00.125576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 53c5de69-0292-4678-be49-fd7533d0c4d3 · outbound

This paper cites MPDP: A probabilistic architecture for microservice performance diagnosis and prediction,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks MPDP: A probabilistic architecture for microservice performance diagnosis and prediction,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-05T22:22:00.114937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 996295e0-b963-4abb-8b0e-8a030425cb1e · outbound

This paper cites AST-GCN: Attribute-augmented spatiotemporal graph convolutional network for traffic forecasting,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks AST-GCN: Attribute-augmented spatiotemporal graph convolutional network for traffic forecasting,

Reference 27

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raw_fallback, observed 2026-08-05T22:22:00.104284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:22:00.007920Z digest=sha256:ef8a018803f8d51852dd3973625e912c47a631e5ae84b2cd44d420a681171d79

Observation 621ec50b-3e2e-4bab-b248-ecbf43b6a54b · outbound

This paper cites Hierarchical dynamic graph convolutional network for spatio-temporal forecasting,.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Hierarchical dynamic graph convolutional network for spatio-temporal forecasting,

Reference 28

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raw_fallback, observed 2026-08-05T22:22:00.092406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:22:00.011616Z digest=sha256:b9714017db41a7b61cae27433d3101b7fb97d38882af3165cdd7f2146f5f0dbf

Observation 0d9c2f40-2462-4f90-9263-f5ca24282fca · outbound

This paper cites Graph WaveNet for Deep Spatial-Temporal Graph Modeling.

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks Graph WaveNet for Deep Spatial-Temporal Graph Modeling

Reference 29

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unresolved
no resolver link, observed 2026-08-05T22:22:00.015034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.