Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:16:15.266342Z
Paper Citation Record · LEDGER
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction
As of 14 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2508.08281.
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 2026-08-13T06:32:02.005865+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
56 of 56 outbound references displayed
- verified exact1
- verified fuzzy51
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 623b7d1a-28c4-4f9b-adfd-747aa61fc541 · outbound
This paper cites Toward 6G TK extreme connectivity: Architecture, key technologies and experiments.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Toward 6G TK extreme connectivity: Architecture, key technologies and experiments
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:17.089713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f4796b5b-03fe-446b-a334-60940dbad8f3 · outbound
This paper cites Deep learning on network traffic prediction: Recent advances, analysis, and future directions.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Deep learning on network traffic prediction: Recent advances, analysis, and future directions
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:17.067167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d2f3ca75-ee87-443b-b243-1cecc0d5556a · outbound
This paper cites Cellular traffic prediction with machine learning: A survey.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Cellular traffic prediction with machine learning: A survey
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:17.035847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6753c120-0c16-4ed4-bcc0-50d0029d6518 · outbound
This paper cites Vu, and Symeon Chatzinotas.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Vu, and Symeon Chatzinotas
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.997797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b5979966-5efa-4062-9cf0-373bd07bf170 · outbound
This paper cites Multi-range bidirectional mask graph convolution based gru networks for traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Multi-range bidirectional mask graph convolution based gru networks for traffic prediction
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.973803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3e7894c4-6f65-448e-bccc-c1c561105ef6 · outbound
This paper cites A novel STFSA-CNN-GRU hybrid model for short-term traffic speed prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A novel STFSA-CNN-GRU hybrid model for short-term traffic speed prediction
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.948057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3ba7d402-e42c-4ecd-8e25-c516b2a5d5ef · outbound
This paper cites A hybrid prediction method for realistic network traffic with temporal convolutional network and LSTM.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A hybrid prediction method for realistic network traffic with temporal convolutional network and LSTM
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.925436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 914c9bf5-c9fa-4ec1-b045-90fe57f3f123 · outbound
This paper cites Informer: Beyond efficient Transformer for long sequence time-series forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Informer: Beyond efficient Transformer for long sequence time-series forecasting
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.878346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 065e655d-3f97-49de-8a2a-e880114a888f · outbound
This paper cites FED former: Frequency enhanced decomposed Transformer for long-term series forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction FED former: Frequency enhanced decomposed Transformer for long-term series forecasting
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.851103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a49f0595-b3d6-427d-99cb-927cf5aa3aa1 · outbound
This paper cites A time series is worth 64 words: Long-term forecasting with Transformers.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A time series is worth 64 words: Long-term forecasting with Transformers
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.813493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4159d5dd-69ab-4007-af9c-c6689c533e68 · outbound
This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.779646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8975f808-f4eb-4ae9-8815-66952a06fa01 · outbound
This paper cites Jointly modeling spatio–temporal dependencies and daily flow correlations for crowd flow prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Jointly modeling spatio–temporal dependencies and daily flow correlations for crowd flow prediction
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.752377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4689286e-f852-4a2d-be00-7ac19fe9e7f0 · outbound
This paper cites Time-wise attention aided convolutional neural network for data-driven cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Time-wise attention aided convolutional neural network for data-driven cellular traffic prediction
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.719683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2aad2257-ed3c-4e55-9049-53eb3d0082f3 · outbound
This paper cites Spatial-temporal aggregation graph convolution network for efficient mobile cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Spatial-temporal aggregation graph convolution network for efficient mobile cellular traffic prediction
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.684429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 03f909d9-3bbe-4701-97a4-fa85f1b1e420 · outbound
This paper cites KST-GCN : A knowledge-driven spatial-temporal graph convolutional network for traffic forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction KST-GCN : A knowledge-driven spatial-temporal graph convolutional network for traffic forecasting
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.651429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4bf6eb64-bf85-4a51-8c6e-824cc3f18e16 · outbound
This paper cites Spatial–temporal graph neural network traffic prediction based load balancing with reinforcement learning in cellular networks.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Spatial–temporal graph neural network traffic prediction based load balancing with reinforcement learning in cellular networks
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.632599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 061b43ea-bed8-4b5a-83db-034082aa570a · outbound
This paper cites Learning multiaspect traffic couplings by multirelational graph attention networks for traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Learning multiaspect traffic couplings by multirelational graph attention networks for traffic prediction
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.607929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5e2b1844-4e20-4f23-963d-9b34d8b7c1a8 · outbound
This paper cites an unresolved cited work.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:16:16.571032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 48a8043f-d91f-4c4f-8a51-cb65ae6c2750 · outbound
This paper cites Spatial-temporal cellular traffic prediction for 5G and beyond: A graph neural networks-based approach.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Spatial-temporal cellular traffic prediction for 5G and beyond: A graph neural networks-based approach
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.543958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d7e51476-8af9-434b-90b8-29aa67c33fdb · outbound
This paper cites A cellular traffic prediction method based on diffusion convolutional GRU and multi-head attention mechanism.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A cellular traffic prediction method based on diffusion convolutional GRU and multi-head attention mechanism
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.504944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3a48e577-1d01-414b-bc04-48d8c924c8d5 · outbound
This paper cites Multi-stream concept drift self-adaptation using graph neural network.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Multi-stream concept drift self-adaptation using graph neural network
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.487559Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 40653fa2-fd21-4138-9aed-e64cdea5c47a · outbound
This paper cites Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:16:14.953639Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf79fa75-832e-4141-a400-f4521122e136 · outbound
This paper cites A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T10:16:15.382631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation aa62a232-e0b4-44ac-a3ec-388369dd5789 · outbound
This paper cites On Tiny Episodic Memories in Continual Learning.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction On Tiny Episodic Memories in Continual Learning
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:16:14.968379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7300be98-73f0-425b-8231-93fb69f8c7c6 · outbound
This paper cites Dark experience for general continual learning: A strong, simple baseline.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Dark experience for general continual learning: A strong, simple baseline
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.446802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d82d87d7-8053-4200-bb30-3c184ea503e3 · outbound
This paper cites TrafficStream : A streaming traffic flow forecasting framework based on graph neural networks and continual learning.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction TrafficStream : A streaming traffic flow forecasting framework based on graph neural networks and continual learning
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.407683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5af0a0f7-fac7-4ee5-9a5e-ce5cb3725609 · outbound
This paper cites Multi-agent deep reinforcement learning-based task scheduling and resource sharing for O-RAN -empowered multi- UAV -assisted wireless sensor networks.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Multi-agent deep reinforcement learning-based task scheduling and resource sharing for O-RAN -empowered multi- UAV -assisted wireless sensor networks
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.374821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e1dc20ed-40bf-4e7f-b0dd-4fb1982c9e30 · outbound
This paper cites Multi-agent DRL -based energy harvesting for freshness of data in UAV -assisted wireless sensor networks.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Multi-agent DRL -based energy harvesting for freshness of data in UAV -assisted wireless sensor networks
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.345281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 795b1e5f-07fa-4ea4-91b3-3554f518b4d9 · outbound
This paper cites Koudouridis, and Per Tengkvist.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Koudouridis, and Per Tengkvist
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.319820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3c9f4bf6-2430-4e63-beb8-96e22babf563 · outbound
This paper cites Data-augmentation-based cellular traffic prediction in edge-computing-enabled smart city.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Data-augmentation-based cellular traffic prediction in edge-computing-enabled smart city
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.297360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 94a4b321-5b8e-45de-ba27-2e2cb6e2fb11 · outbound
This paper cites Deep transfer learning for intelligent cellular traffic prediction based on cross-domain big data.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Deep transfer learning for intelligent cellular traffic prediction based on cross-domain big data
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.274267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 36c361b3-728c-40d5-8a46-e205287e797d · outbound
This paper cites STEP : A spatio-temporal fine-granular user traffic prediction system for cellular networks.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction STEP : A spatio-temporal fine-granular user traffic prediction system for cellular networks
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.241402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ddc7d819-5d92-42f8-b2d3-512fe944d1c4 · outbound
This paper cites Graph attention spatial-temporal network with collaborative global-local learning for citywide mobile traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Graph attention spatial-temporal network with collaborative global-local learning for citywide mobile traffic prediction
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.216221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2a615fdd-aded-4bff-a881-de83a48a6b65 · outbound
This paper cites Lui, and Xiaohong Guan.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Lui, and Xiaohong Guan
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.167487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation aa37c112-11bc-49ff-9379-1e5c7e92a518 · outbound
This paper cites Spatio-temporal parallel transformer based model for traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Spatio-temporal parallel transformer based model for traffic prediction
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.137178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 27214a4b-bb07-4c92-8eb0-dea8d8f8a317 · outbound
This paper cites Adaptive graph spatial-temporal Transformer network for traffic forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Adaptive graph spatial-temporal Transformer network for traffic forecasting
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.111883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d9f2956d-cfb9-4b73-be55-e2684b7c9304 · outbound
This paper cites FGITrans : Cross-city Transformer for fine-grained urban flow inference.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction FGITrans : Cross-city Transformer for fine-grained urban flow inference
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.088521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5c93cd9b-f670-46a7-a7cf-dfe1cc8919d2 · outbound
This paper cites an unresolved cited work.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Unresolved cited work
Reference 38
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:16:16.057347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 30de3f1a-f026-467f-8157-def40ee67b82 · outbound
This paper cites Multi-behavior sequential recommendation with temporal graph transformer.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Multi-behavior sequential recommendation with temporal graph transformer
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:16.023834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 90603dfe-ab57-426b-80da-9db3a134d713 · outbound
This paper cites Spatial-temporal attention-convolution network for citywide cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Spatial-temporal attention-convolution network for citywide cellular traffic prediction
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.987259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 341f7459-187d-4ff4-bafe-8608601ef6cb · outbound
This paper cites ST-Tran : Spatial-temporal Transformer for cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction ST-Tran : Spatial-temporal Transformer for cellular traffic prediction
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.959341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e4440f8d-9d9f-4faa-b5cd-53c40bf69687 · outbound
This paper cites MVSTGN : A multi-view spatial-temporal graph network for cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction MVSTGN : A multi-view spatial-temporal graph network for cellular traffic prediction
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.911634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8be842a9-eb5d-49c8-bb60-00a6b46b6d54 · outbound
This paper cites A spatial-temporal Transformer network for city-level cellular traffic analysis and prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A spatial-temporal Transformer network for city-level cellular traffic analysis and prediction
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.884690Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a6d5b548-908f-4a21-9e85-ac8a8431b0f1 · outbound
This paper cites STMGF : An effective spatial-temporal multi-granularity framework for traffic forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction STMGF : An effective spatial-temporal multi-granularity framework for traffic forecasting
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.859490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f5de93b4-d432-4d04-b4bb-9c4853dd2067 · outbound
This paper cites Dynamic multi-granularity spatial-temporal graph attention network for traffic forecasting.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Dynamic multi-granularity spatial-temporal graph attention network for traffic forecasting
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.814174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ff453ccf-84fd-46fd-a39a-ebb90ae02fdb · outbound
This paper cites Lifelong online learning from accumulated knowledge.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Lifelong online learning from accumulated knowledge
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.784168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 029275ac-2112-44fc-b974-e5549ba44002 · outbound
This paper cites Online continual learning with maximal interfered retrieval.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Online continual learning with maximal interfered retrieval
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.752834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation cf91475f-4b6a-43d5-a6bf-2ad1640e0018 · outbound
This paper cites OneNet : Enhancing time series forecasting models under concept drift by online ensembling.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction OneNet : Enhancing time series forecasting models under concept drift by online ensembling
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.725511Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 81164b0f-ffd9-4b52-a5d4-db72f9c4b823 · outbound
This paper cites LNTP : An end-to-end online prediction model for network traffic.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction LNTP : An end-to-end online prediction model for network traffic
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.681464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f2f6efbe-249c-44c6-89d2-e8cb3e838b43 · outbound
This paper cites A multi-source dataset of urban life in the city of Milan and the province of Trentino.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A multi-source dataset of urban life in the city of Milan and the province of Trentino
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.643139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ee7c56ef-bde2-4bbe-b6ea-67dc5a7f3e7d · outbound
This paper cites Dynamic modification neural network model for short-term traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Dynamic modification neural network model for short-term traffic prediction
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.621051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 703a7de6-1498-4ccc-868a-37967aa1cd3b · outbound
This paper cites A novel short-term traffic prediction model based on SVD and ARIMA with blockchain in industrial Internet of things.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A novel short-term traffic prediction model based on SVD and ARIMA with blockchain in industrial Internet of things
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.591582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c06005e5-22bb-4426-a37f-ab66486f0530 · outbound
This paper cites Attention is all you need.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Attention is all you need
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.558983Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4b8df8ac-523c-4f05-9e2c-02754c19d45f · outbound
This paper cites Adaptive hybrid spatial-temporal graph neural network for cellular traffic prediction.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Adaptive hybrid spatial-temporal graph neural network for cellular traffic prediction
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.506610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5c471c15-e224-4024-9f19-c965594229bf · outbound
This paper cites Towards dynamic spatial-temporal graph learning: A decoupled perspective.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Towards dynamic spatial-temporal graph learning: A decoupled perspective
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.483766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e96d66ff-ca31-4f3f-8da8-2fb52d796f63 · outbound
This paper cites Machine learning for 6G enhanced ultra-reliable and low-latency services.
Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction Machine learning for 6G enhanced ultra-reliable and low-latency services
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:16:15.441000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Pith citing papers
No inbound Pith citation observations are available.