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Paper Citation Record · LEDGER

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction

As of 8 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2507.17795.

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

pith.paper-citation-record.v1
2507.17795 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:52:30.425255Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T02:44:19.395548Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

70 of 70 outbound references displayed

  • verified exact1
  • verified fuzzy51
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d596a77-a2e3-485f-9766-50ffd82dafee · outbound

This paper cites Kgda: A knowledge graph driven decomposition approach for cellular traffic prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Kgda: A knowledge graph driven decomposition approach for cellular traffic prediction,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 482a3fb5-c132-4831-b07b-0bc9d0eaaa5f · outbound

This paper cites Safe-nora: Safe reinforcement learning-based mobile network resource allocation for diverse user demands,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Safe-nora: Safe reinforcement learning-based mobile network resource allocation for diverse user demands,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 2f46bb2e-032d-4785-a469-4b0c5cc1f3e9 · outbound

This paper cites Dynamic channel allocation scheme based on traffic prediction in dense wireless networks,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Dynamic channel allocation scheme based on traffic prediction in dense wireless networks,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 666e001f-1f05-456f-aa5c-d8b81b6dcd5e · outbound

This paper cites Carbon emissions of 5g mobile networks in china,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Carbon emissions of 5g mobile networks in china,

Reference 4

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raw_fallback, observed 2026-08-06T14:52:31.001373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b3e3cef9-9c76-4d6b-a600-1fff8b0d594c · outbound

This paper cites Artificial intelligence for reducing the carbon emissions of 5g networks in china,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Artificial intelligence for reducing the carbon emissions of 5g networks in china,

Reference 5

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raw_fallback, observed 2026-08-06T14:52:30.992899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c73f8125-1247-400e-8c41-d8caad9141d9 · outbound

This paper cites Mobile traffic prediction from raw data using lstm networks,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Mobile traffic prediction from raw data using lstm networks,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 36a6aa95-8cc7-4fa8-9388-11a1bff05725 · outbound

This paper cites Deeptp: An end-to-end neural network for mobile cellular traffic prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Deeptp: An end-to-end neural network for mobile cellular traffic prediction,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.247606Z digest=sha256:d8fc0e4fe22ae6f9396ee333a59e7012e6f11601aeb39d00ad5b9e831b74ea42

Observation c56dea9f-3691-4c49-9490-2da22ee6e6ca · outbound

This paper cites Spatial- temporal cellular traffic prediction for 5g and beyond: A graph neural networks-based approach,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Spatial- temporal cellular traffic prediction for 5g and beyond: A graph neural networks-based approach,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.250397Z digest=sha256:5872004e2903e2c95e606bee2bf19d9f1497524bee052cacfe13c3947b6b702e

Observation 2389ee2f-adae-4774-90c1-d1865d826bdb · outbound

This paper cites Empowering spatial knowledge graph for mobile traffic prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Empowering spatial knowledge graph for mobile traffic prediction,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 338741ad-5121-40fd-852b-7ef43d5d26f1 · outbound

This paper cites Sdgnet: A handover-aware spa- tiotemporal graph neural network for mobile traffic forecasting,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Sdgnet: A handover-aware spa- tiotemporal graph neural network for mobile traffic forecasting,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8062db49-169f-435d-9e53-87b21d63aa53 · outbound

This paper cites To what extent we repeat ourselves? discovering daily activity patterns across mobile app usage,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction To what extent we repeat ourselves? discovering daily activity patterns across mobile app usage,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dcc05820-8fec-4109-8389-a47310d8abdc · outbound

This paper cites Atpp: A mobile app prediction system based on deep marked temporal point processes,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Atpp: A mobile app prediction system based on deep marked temporal point processes,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.261882Z digest=sha256:f4d9d09e2fc34c26f9ff4d1beb01dfc49e35f64ede982f42218f0fadf7a18644

Observation 1acd2ed6-a7cf-48b1-8b81-de4717ffb5dc · outbound

This paper cites On mining mobile apps usage behavior for predicting apps usage in smartphones,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction On mining mobile apps usage behavior for predicting apps usage in smartphones,

Reference 13

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raw_fallback, observed 2026-08-06T14:52:30.919868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.264584Z digest=sha256:26971a76a4486a6560e1f7b6994c562bbb7acf2652ed8b5a031f30ad2ef69788

Observation 70e41f19-9a44-493e-83df-0c1c33a49955 · outbound

This paper cites Fundamentals of recurrent neural network (rnn) and long short-term memory (lstm) network,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Fundamentals of recurrent neural network (rnn) and long short-term memory (lstm) network,

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.267210Z digest=sha256:c02f845c9aafc90e136a84ff35a7ce2007648580b33a6739325e337a1c551009

Observation c8ca2f43-4af8-490e-a113-290cb9adbfc0 · outbound

This paper cites Diffusion models in vision: A survey,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Diffusion models in vision: A survey,

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1629446b-3391-4029-8860-f5e70650deb8 · outbound

This paper cites Exploiting geographical influence for collaborative point-of-interest recommendation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Exploiting geographical influence for collaborative point-of-interest recommendation,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4a3b4439-7bc2-4dc4-9acc-83b101751bfe · outbound

This paper cites Netdiff: A service-guided hierarchical diffusion model for network flow trace generation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Netdiff: A service-guided hierarchical diffusion model for network flow trace generation,

Reference 17

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raw_fallback, observed 2026-08-06T14:52:30.891924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.275659Z digest=sha256:e36bf75d2c3eff7d9573d6480bc71bd8d66936b19b2e715d5563393ddaa60432

Observation 3ca901f2-a368-4106-826c-a5a05fffeed9 · outbound

This paper cites Cellular traffic prediction with machine learning: A survey,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Cellular traffic prediction with machine learning: A survey,

Reference 18

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raw_fallback, observed 2026-08-06T14:52:30.883294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation df67170c-b2c0-42e6-baa9-5995323a35c1 · outbound

This paper cites Mobile traffic prediction in consumer applications: a multimodal deep learning approach,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Mobile traffic prediction in consumer applications: a multimodal deep learning approach,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.281175Z digest=sha256:22f98d7a68ac6634ea94c154828c5b74971748c98e9c6eecdb456a0da3b0dd5b

Observation b517f8ac-3b64-43dd-b858-5709d965f989 · outbound

This paper cites Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.283831Z digest=sha256:4c234b38781701113c1182bf31a3171d275a1ecb3f64ca1064a30d0311f9fc50

Observation 0782b1ff-ef4b-4412-ba04-deede76065d4 · outbound

This paper cites Attentive crowd flow machines,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Attentive crowd flow machines,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.286841Z digest=sha256:d6a7e85963b2b16e29dc7a76228c40fb0e6c6e31f27227836b2d1634e107b762

Observation d6f613ad-36bd-4932-b8da-07189f4f6671 · outbound

This paper cites Deep spatio-temporal residual networks for citywide crowd flows prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Deep spatio-temporal residual networks for citywide crowd flows prediction,

Reference 22

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raw_fallback, observed 2026-08-06T14:52:30.857693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8d17f852-1d04-48e5-95c3-c5c980abc22b · outbound

This paper cites Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning,

Reference 23

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raw_fallback, observed 2026-08-06T14:52:30.849415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.292202Z digest=sha256:3f5a48c20d56077525ef731e6bfd3db5bcff5bbfb473d3830725b772e7d26214

Observation d16067a4-b4fd-49c7-969e-ff168b0aa790 · outbound

This paper cites Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms,

Reference 24

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raw_fallback, observed 2026-08-06T14:52:30.841153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.294700Z digest=sha256:c1023c8762f92c7f1cbaa2042344a3c9535c21cf2cffa6bfeb98eff3ca63236f

Observation 3843c212-ec54-4e15-81b1-cf7d3a4e7654 · outbound

This paper cites Graph attention spatial- temporal network with collaborative global-local learning for citywide mobile traffic prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Graph attention spatial- temporal network with collaborative global-local learning for citywide mobile traffic prediction,

Reference 25

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raw_fallback, observed 2026-08-06T14:52:30.832672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6e5e0f8f-14ae-4476-8297-f4813ce6e809 · outbound

This paper cites Transformer-based spatio-temporal traffic prediction for access and metro networks,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Transformer-based spatio-temporal traffic prediction for access and metro networks,

Reference 26

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raw_fallback, observed 2026-08-06T14:52:30.824285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.299978Z digest=sha256:fec6c02cbfe3b474769429212778b9c6cc9c68c61ddaf254da30ea33b679cacb

Observation dbcdb904-ad56-4d65-8278-1d562bb273dd · outbound

This paper cites Spatio-temporal graph transformer networks for pedestrian trajectory prediction,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Spatio-temporal graph transformer networks for pedestrian trajectory prediction,

Reference 27

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raw_fallback, observed 2026-08-06T14:52:30.815766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.302761Z digest=sha256:c3446ca30fbea4115c13ee8a86470d81db2e499281537e23bb099d2cd0cbd7c7

Observation 8b03a829-90f7-45dd-aa32-6f5be20108da · outbound

This paper cites Transformer based traffic flow forecasting in sdn- vanet,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Transformer based traffic flow forecasting in sdn- vanet,

Reference 28

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raw_fallback, observed 2026-08-06T14:52:30.807718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.305763Z digest=sha256:a3647eddd1aaaa4a52b3d81c0b8168d1dedf0087bd3f267f591045891e1d6df3

Observation 8af82261-c32c-448d-bb01-e6b804664057 · outbound

This paper cites Mobile network traffic prediction using mlp, mlpwd, and svm,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Mobile network traffic prediction using mlp, mlpwd, and svm,

Reference 29

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raw_fallback, observed 2026-08-06T14:52:30.798728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.308446Z digest=sha256:6db9bed849a751147ca03ba40ff690c96ca0385fafcc5a1e14eae818b36d8f8c

Observation c74e0c4d-d2b8-4d5a-b582-815d43c95b9d · outbound

This paper cites Characterization and prediction of mobile-app traffic using markov modeling,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Characterization and prediction of mobile-app traffic using markov modeling,

Reference 30

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raw_fallback, observed 2026-08-06T14:52:30.789482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.311049Z digest=sha256:aa9e5d1c41039c02a66d0450256c59eab85386cd960837ec53ce08fe70563248

Observation b5f4a88b-c5ac-4134-9fe5-a99311d9d608 · outbound

This paper cites Spatio-temporal diffusion point processes,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Spatio-temporal diffusion point processes,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.780722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.313641Z digest=sha256:0c68bbf7c9295575b8ea1b9307f84584d12c47fb4efa8f51272fa5da60cfc3e9

Observation cb00cdf8-d632-4481-8d24-fb851b2fd2fd · outbound

This paper cites Towards generative modeling of urban flow through knowledge-enhanced denoising diffusion,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Towards generative modeling of urban flow through knowledge-enhanced denoising diffusion,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.771936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.316331Z digest=sha256:9d46c36eb362ed7de0ac624ffb12a22bcddb476a6b1ae35a333029547dc608c6

Observation 3d34985b-d35d-4931-bda4-c30d148cc6fc · outbound

This paper cites Network traffic prediction based on diffusion convo- lutional recurrent neural networks,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Network traffic prediction based on diffusion convo- lutional recurrent neural networks,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.319627Z digest=sha256:48bff9f81368c8675c1d086da60be5124d56379fcfe55abff530fec6f32aff27

Observation 7e58d410-a982-45d0-83da-9696e6d4afe0 · outbound

This paper cites Spatio-temporal knowledge driven diffusion model for mobile traffic generation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Spatio-temporal knowledge driven diffusion model for mobile traffic generation,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.322278Z digest=sha256:887eb82b924e7ab9a006eebc41b20bbc0e74930b25b29be35cd25e0988c72e8e

Observation a77fa932-f978-4148-be9c-4098829681cd · outbound

This paper cites Practical gan-based synthetic ip header trace generation using netshare,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Practical gan-based synthetic ip header trace generation using netshare,

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.325006Z digest=sha256:1e25e5c26fca67c27d725420f319e315f9f5594a59f13c3f86d3c62e59b63a1b

Observation 13e1a435-4a08-49d0-8dc4-d10a5acf3310 · outbound

This paper cites Mobile user traffic generation via multi-scale hierarchical gan,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Mobile user traffic generation via multi-scale hierarchical gan,

Reference 36

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raw_fallback, observed 2026-08-06T14:52:30.740508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.327727Z digest=sha256:5e8c6c26c1a266701c15af5000cc098b5236ac8dc42f5cd3edd7ad83224cc432

Observation c9d0c458-de68-489c-9816-e23eb44f25fc · outbound

This paper cites Mobile data traffic prediction by exploiting time-evolving user mobility patterns,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Mobile data traffic prediction by exploiting time-evolving user mobility patterns,

Reference 37

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raw_fallback, observed 2026-08-06T14:52:30.732396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.330608Z digest=sha256:9dfe2755947d692d1a738eca60f2eeae0a088e14612067a166985198d902af35

Observation 51331746-8f6f-49d4-a643-d07bfb493b30 · outbound

This paper cites Conditional Image Generation with Score-Based Diffusion Models.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Conditional Image Generation with Score-Based Diffusion Models

Reference 38

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no resolver link, observed 2026-08-06T14:52:30.333174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.333174Z digest=sha256:1bd9bd25c05dbbe493580405c7d1dcfa64ff247fbac289561257d8e00a757afb

Observation c1de19e6-b402-4847-b098-b8534928b8e0 · outbound

This paper cites scdiffusion: conditional generation of high-quality single-cell data using diffusion model,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction scdiffusion: conditional generation of high-quality single-cell data using diffusion model,

Reference 39

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raw_fallback, observed 2026-08-06T14:52:30.724105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.336101Z digest=sha256:3cfc03c4e73b5ca5a27b323446873feb150418c0d3eefc60a80460adb6ef4663

Observation ef4a9845-5647-4d9c-a910-691174dbbb30 · outbound

This paper cites Netdiffus: Network traffic generation by diffusion models through time-series imaging,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Netdiffus: Network traffic generation by diffusion models through time-series imaging,

Reference 40

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raw_fallback, observed 2026-08-06T14:52:30.714697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.339227Z digest=sha256:c7e02e8d0cf74bd4be877bd00f0a7bd33a4731f0a1f3a280714dda432db513fa

Observation 1f8640d4-f12f-4864-a175-b55c12106288 · outbound

This paper cites Pcapgan: Packet capture file gen- erator by style-based generative adversarial networks,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Pcapgan: Packet capture file gen- erator by style-based generative adversarial networks,

Reference 41

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raw_fallback, observed 2026-08-06T14:52:30.704880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.342041Z digest=sha256:43ba64ca57ae3c4ddc2a7a132cba01bc2e1646e9b2ed90dfd8d604fbbedaaad7

Observation 81cdf536-6fe4-48eb-b57d-df9b21fbd680 · outbound

This paper cites Large Language Models: A Survey.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Large Language Models: A Survey

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.344769Z digest=sha256:54ef2f4214e47b4941311b06306141d5461e1e834be2d09c056b8eeb1a529ca8

Observation 2adfa8dd-3e6e-435d-8bee-0167cf05a8e0 · outbound

This paper cites Clip and complementary methods,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Clip and complementary methods,

Reference 43

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raw_fallback, observed 2026-08-06T14:52:30.695669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.347645Z digest=sha256:9d66f1f3df3f9d613c6bb4ab86b81b5aba848b41a780b8e0f9673ff0fc9967aa

Observation 3424e544-b730-4008-9aed-f869d2cb2814 · outbound

This paper cites Contrastive learning of medical visual representations from paired images and text,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Contrastive learning of medical visual representations from paired images and text,

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.687094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.350354Z digest=sha256:a504fdbb56fb1981eb5ec833536f762e6adab4765c699c812c059b13472f1f8a

Observation e12e45ea-e0e2-4aeb-b837-1ef066495a93 · outbound

This paper cites Pubmedclip: How much does clip benefit visual question answering in the medical domain?.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Pubmedclip: How much does clip benefit visual question answering in the medical domain?

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.678509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.352911Z digest=sha256:1133ce38f8539c9068ac6405fb431f061a8702da46624a2239754ae79b439888

Observation b3a9437b-054d-4430-b2b7-d30a91b6fa42 · outbound

This paper cites MedCLIP: Contrastive Learning from Unpaired Medical Images and Text.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction MedCLIP: Contrastive Learning from Unpaired Medical Images and Text

Reference 46

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.355550Z digest=sha256:bf1083fec0b4c0b7e44dcc67fcee9cbf1687a24c4be16ed60f424c99c45ca244

Observation 29f1039b-8118-469f-9030-5ffbfe08f020 · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.358453Z digest=sha256:7f8e37e7fccad91ae1396c8311d30dfac924c4d8d0df4d49fbf7de091469e704

Observation 1a150cc0-bdc6-49b6-854b-4a959281a48d · outbound

This paper cites Remoteclip: A vision language foundation model for remote sensing,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Remoteclip: A vision language foundation model for remote sensing,

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.361475Z digest=sha256:5478ee999f8e2eff07ca322f09f194bc3e84cc20d3c7e8df234ecae973965fd1

Observation f0ecf7bf-e081-4593-8b40-1a00576c36a0 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Diffusion models: A comprehensive survey of methods and applications,

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.363998Z digest=sha256:15b2335b3d468efad6a17135a0a6cd0949825e8485e1c3c35ae0e2761e5b12a4

Observation 2ed88d33-cd88-4c23-a33b-68593143e07b · outbound

This paper cites How Much Can CLIP Benefit Vision-and-Language Tasks?.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.367048Z digest=sha256:04a9b7f994f50bfb975e1612e023cfcf6427465762153287fc1d2076b6ec952d

Observation 7d37b8c6-015e-4dbe-b1a9-5d88f531a5c4 · outbound

This paper cites Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web,

Reference 51

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raw_fallback, observed 2026-08-06T14:52:30.659666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.370209Z digest=sha256:250c517300249ca75017db224c0d7408b451025b0e3f6ee6cbe9229d00b0eb61

Observation 71d3ccca-9c03-4b40-9241-322eb84ab13b · outbound

This paper cites Enhancing multi- modal understanding with clip-based image-to-text transformation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Enhancing multi- modal understanding with clip-based image-to-text transformation,

Reference 52

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.373484Z digest=sha256:d0dfa6429c99ff534356b24a5d0471244c79ec8289224f05467792aa2f7a1fba

Observation ca03d061-884e-4707-9cf0-b9cbf1692876 · outbound

This paper cites Forecasting long-term spatial-temporal dynamics with generative transformer networks.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Forecasting long-term spatial-temporal dynamics with generative transformer networks

Reference 53

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.376274Z digest=sha256:cdeb96405a8c9ba955aeb801a36ef89fb402fa2fdcbcec8a48f2859a12fdb327

Observation 75019fac-709b-41b4-8f3c-5c876310c937 · outbound

This paper cites Long-Range Transformers for Dynamic Spatiotemporal Forecasting.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Long-Range Transformers for Dynamic Spatiotemporal Forecasting

Reference 54

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T14:52:30.379718Z digest=sha256:de59b5919e720f5518d20c0321a52aa472c8efa1f5aedf73366800db552eea34

Observation a3b9ca40-afe7-4e90-bade-4f135aacb453 · outbound

This paper cites Poster: A one-size-fits-all solution for cross-technology communication via transformer,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Poster: A one-size-fits-all solution for cross-technology communication via transformer,

Reference 55

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.382553Z digest=sha256:415ca54f43583be5a7fc652208caf361730866dfbf2a7859505f0fd82f29f05d

Observation faf65947-94aa-4775-a1a1-6f0745da3250 · outbound

This paper cites Multimodal condi- tioned diffusion model for recommendation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Multimodal condi- tioned diffusion model for recommendation,

Reference 56

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raw_fallback, observed 2026-08-06T14:52:30.626668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.385212Z digest=sha256:90b972991c14da7a14b3c9cab9f3b12fad81ffceea1a705321f3285583b51386

Observation eee34581-edbb-433e-ac83-d5ea91e10ba2 · outbound

This paper cites Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Model.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Model

Reference 57

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local_arxiv, observed 2026-08-06T14:52:30.504214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.387941Z digest=sha256:78bc5aeeb9e707aedafcceb38f78226eef80556656bfe12af2d3bb490a122174

Observation 162d3657-f430-4720-bd3b-3e57cd9adc80 · outbound

This paper cites Latent diffusion transformer for probabilistic time series forecasting,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Latent diffusion transformer for probabilistic time series forecasting,

Reference 58

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raw_fallback, observed 2026-08-06T14:52:30.618682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.390871Z digest=sha256:c7da99acb370607361d2c306ae6e276fbc74248632e0762fe974d95c52c0f6e5

Observation bc875865-23ec-4d0a-8c9c-318b9df21e4f · outbound

This paper cites FiT: Flexible Vision Transformer for Diffusion Model.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction FiT: Flexible Vision Transformer for Diffusion Model

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.393598Z digest=sha256:122abf993eada753c48b01953a90f3258eaf7ff81c5e06b4d858022f93d30660

Observation 81b85b49-4af9-40d2-be5c-f37b607df58f · outbound

This paper cites Samples: Self adaptive mining of persistent lexical snippets for classifying mobile application traffic,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Samples: Self adaptive mining of persistent lexical snippets for classifying mobile application traffic,

Reference 60

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raw_fallback, observed 2026-08-06T14:52:30.610277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.396669Z digest=sha256:6b5d11df982dafbe02cb8b23db5a4fdffecdcef72f582068aa79b819edc1064c

Observation e9cde03a-116d-4566-a045-860197779f33 · outbound

This paper cites Machine learning for interconnect network traffic forecasting: Investigation and exploitation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Machine learning for interconnect network traffic forecasting: Investigation and exploitation,

Reference 61

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raw_fallback, observed 2026-08-06T14:52:30.600979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.399830Z digest=sha256:36adc401efde5d3e89f9ade6742e28494eda0719a7ebf8ff1278d876ec29f4d3

Observation 0a1e5efe-ee16-46f1-b5b1-ae1ef6b27901 · outbound

This paper cites TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 62

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.402593Z digest=sha256:7a3fd8a5cb1b19879d72727f9243ad3a5138976c7fa7d2064a3a59ff331f08b4

Observation 3a0ea26e-939d-4f58-a5b3-29e553196b43 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.405503Z digest=sha256:166b62e2fbd16560a25c30e9e86b0149da1658581c81bcb695819e670275c1fa

Observation bbafa8bb-ca8a-4068-8097-76f20feddd0e · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.408394Z digest=sha256:796cfc0b8f958bed686ce6d8d32c0093d39bb277f7e9215d4fece0f7af75ebc6

Observation 110c11bb-d51a-4b14-82db-154309306ce1 · outbound

This paper cites Scalable diffusion models with transformers,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Scalable diffusion models with transformers,

Reference 65

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raw_fallback, observed 2026-08-06T14:52:30.592837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.411289Z digest=sha256:21c4285e0bed5ba46860731ac28c1fdde8bb8c0634108d3af2f1f35019089b6c

Observation 641a3f35-b8bd-4ea4-9cfa-709ee27144f2 · outbound

This paper cites Csdi: Conditional score- based diffusion models for probabilistic time series imputation,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Csdi: Conditional score- based diffusion models for probabilistic time series imputation,

Reference 66

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raw_fallback, observed 2026-08-06T14:52:30.584682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.414114Z digest=sha256:1bd10be648486b437bcc778667ecfad7fa8c644ffeeb85b90a8505c8e16d4bff

Observation 2080ae6a-e7c9-447e-ab60-5f2b65b883f4 · outbound

This paper cites Rf-diffusion: Radio signal generation via time-frequency diffusion,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction Rf-diffusion: Radio signal generation via time-frequency diffusion,

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.575965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.416855Z digest=sha256:e81a2e9008215f057a4fc713bdf4dd72afbf15a215faf7a81ce6a657ae8f6c2e

Observation 4f3090a5-4eac-41c2-bc49-2446256dc555 · outbound

This paper cites ChatGPT,.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction ChatGPT,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:52:30.567625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T14:52:30.419562Z digest=sha256:54788cad9b29a878677d8eee8264f5183398698e8877d2288e6d7c5c74eb5074

Observation 23dc3bce-dcb4-4c57-9cdc-1519d57cc4e6 · outbound

This paper cites GPT-4 Technical Report.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction GPT-4 Technical Report

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T14:52:30.422403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.422403Z digest=sha256:f16d0a5cfa8204341a9d0049d44230ad6ce5203c60a264cb352dece2fec21eba

Observation 9e3c72b1-a1a3-4727-9f68-02f88100ed1e · outbound

This paper cites GPT-4o System Card.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction GPT-4o System Card

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T14:52:30.425255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.425255Z digest=sha256:603f6f1dce01f103481fdba1e5d0e43d13da3bf2d8cbfef9db05070176e20efe

Pith citing papers

Observation beb09dde-006c-4f42-b535-ee9f6ea04430 · inbound

MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion cites this paper.

MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-02T02:44:19.395548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:44:19.395548Z digest=sha256:772fc3b81b783abe95294865c6c3a69fec9c88f3be5700f1ac8a67421d2e70e2