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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.247606Z digest=sha256:e37427402d8d80fc2c10a950bc216a60beefbc4a94efc45213d391ab1215e7fa

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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raw_fallback, observed 2026-08-06T14:52:30.966683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.250397Z digest=sha256:a9f9de25ead92118b533a9cb910d6c0b2b9420167ed423b66320be76f1b42c1b

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 2026-08-07T06:34:17.273281+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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raw_fallback, observed 2026-08-06T14:52:30.948199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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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raw_fallback, observed 2026-08-06T14:52:30.930230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.261882Z digest=sha256:bc0707c5727fb8d510314c299cc00ce361b4a124be7243be05b92a77a2816779

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.264584Z digest=sha256:0f26707cfc9cb1fc30f1228137e31a0a0abb97a124dcd9b60fff8eaf9f40f9bb

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.

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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.

source=pdf_text observed=2026-08-06T14:52:30.269919Z digest=sha256:9783337817c721f1a282e7bf2b3e39eabd9bedbb85e63ec5e6bf4d7ca990ff1f

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 2026-08-07T06:34:17.273281+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+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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raw_fallback, observed 2026-08-06T14:52:30.874101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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:e49a116b58a25ceec107011885e24ea5b4ce1d4521f151d372693fe1c98104a9

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 2026-08-07T06:34:17.273281+00:00.

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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

Resolution
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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.289634Z digest=sha256:9f738b9001307185ccf126bf34fa95784498a39dc55d026dcd0d42a58220fd55

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 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.299978Z digest=sha256:b70f9b91ab0c375e48404dbe0ce619a511f11ff435e724c20ba3dae927be8068

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.302761Z digest=sha256:0ac77572ac8f1ce200386435223ba18cc8e96fb1ccd94891024738ec70e1b18a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.305763Z digest=sha256:5c371ea8e78535ef6d08cdc8e867a8d6c8a1294dece0b1b1e0bc865c914349b4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.308446Z digest=sha256:abe9adfd1a5a92a1904c6c120c8acb1cacffe24c817f077b0628b3fcb380e75d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.311049Z digest=sha256:ba3e371c1ee8f48a541935291881c806bdc6b6d5a2e016b9bdb321a4b1772645

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.313641Z digest=sha256:025857d20f7acb10b39935a520ccd75aff3d670012de9a419ea35c22d8f69d51

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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.316331Z digest=sha256:e150cbff23d1a172209a9044d6ec06c2e4521d4aafa0f4aa984a8ea19f62da93

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.319627Z digest=sha256:0992e8c0499456c72e7a795b831d315f3a474c5177fee0021e120dbfc3dacd26

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.322278Z digest=sha256:019578f69c656335ee32dcecb43ec67bad3f8e5b5a07606b409aaedd4f4c2e68

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=sha256:3bf09ef1f2e85e2f7f51135ce49b2443c8702521f62efbaa22706a6ff80252ca

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.327727Z digest=sha256:3efa14466ea22b119bd049fa7d934971619df77a8839c0d38ce378d277af9168

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.330608Z digest=sha256:f8b005eeb0b1e2200c4d8a3657f1aa742b006b494b2e02345c32f0751af6f632

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.333174Z digest=sha256:f22db1d7c5d3b7a395bc38ff3506ecf685e15baa260358b9dcc462efaa6ed7d8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.336101Z digest=sha256:c0018fa274c6de6fb4b478846f0f51042c043b1a12624166ffe81668837b5a46

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.339227Z digest=sha256:f4dcecfa6029fd3b57651182658400afc98694542dc397670d2f51101cbccaf5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.342041Z digest=sha256:1420f13217800cd7a56efd863ba6d201cf3a816545fbe68dd39767b748a7cfc3

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=sha256:5e1bed6835f9fd8fb17226f9336fab9fbf505d567f4518f998d63ff04cbd2057

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.347645Z digest=sha256:1469f178ba2a4912cd6c643deff7f83415294ce36bce4036cd75e9e5e7fe352b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.350354Z digest=sha256:524fa72178d02748b7cc293204c79ca25f562d5de6484adbfc47f66da0d88578

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.352911Z digest=sha256:333b5c801fe95f7271b33a30cfce03388c41a0436f3b13960e04b53ab7e59feb

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:a91c4f800d1d4c1ab3666c8e8704236ee8fbf0787d8b5fc94a9e408d2213d44c

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=pdf_text observed=2026-08-06T14:52:30.358453Z digest=sha256:daa8472ff5f2692a23519a62ba5cb7be14799469f4b448f0191fc195ea483db9

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=pdf_text observed=2026-08-06T14:52:30.361475Z digest=sha256:c427f3fe987af7ee9364697733c2b3c3183c8fa8eac3a5ac253fb980ee672661

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=sha256:0798e91994713db5d1d53874634744661bd3f26e988a0c07f78b3fc0a58849bb

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=sha256:68e18233b59bbaf513d3d19f855fbe584adc059b80f6b7dc7bc0ac6a412c9c4e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.370209Z digest=sha256:bbc7909e9ff89e2e10168a433281abcc5cb87aaee9d958757800bf4b5f5516c1

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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raw_fallback, observed 2026-08-06T14:52:30.651255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.373484Z digest=sha256:9a79f7b3e2e29db441aa3698f6b434d7a340ad11b529264988adadd4c719d85d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.376274Z digest=sha256:8cd63a63b90742bfb15d1be72acdd0631a971332cf756898439fdc96b9b1efcd

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=pdf_text observed=2026-08-06T14:52:30.379718Z digest=sha256:a41f64cb46aaa5201bd372cb31834bb58cc65838a45fa497676ade2a699744a2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.382553Z digest=sha256:fce62d16109a1fa56636a3ef9d94db070d795f7e3fd4d6481e4b95ee58602526

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.385212Z digest=sha256:41f71a04c956156a100838ec522170af5e92ad7211d36021f9f24b6a8cc6a538

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.387941Z digest=sha256:87345cabba95f9f2a0a39f8d0b90d7dc6aa8a39ba60716f30d55cc87c4a40c21

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.390871Z digest=sha256:ff6140cae0623492ccaafd58c98883bd62f11916cfe1c05f4460f935788a833b

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:e9fe39cfa0f350a4a576b66de310d5df696f7cccaa1550bdb89e34883918ac55

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.396669Z digest=sha256:04c462ef4b25eeab8f7d49f47207670a69d24cadd480bc8719f5601140dc2a29

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.399830Z digest=sha256:c975ba86c6b44f873c47f0f81a9c1987bbb2702fd1bc447b1f7f313aa09d47ba

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:d00d2add5d9580bc6e31ab8a62168fa59c8d7adc30dffa6c73dcb4c483d81fcc

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=sha256:017bee631929e832d54828693151cf2e4d2987fca51ac68b6018d6ccbaaf3e70

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=sha256:5e96f7dc8c61a02f80edba2c382b4abb31c28db26b4b10077dcc9814027fd520

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.411289Z digest=sha256:2750c51a661aa08c434fc95b1f251f9f571730beaf62c7515b9e84c5de40cfbb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.414114Z digest=sha256:433945d436e5e519266c693f0260650988f2a79ddb66867b60db54a6836ab3eb

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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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.416855Z digest=sha256:74d9c673a507d09f8ee20e626e7d43e02d3e8af381b9235c2c1bbf826629479e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:52:30.419562Z digest=sha256:63ee52849c5b0745e033699c31db242addb7dfbbf4e021229da0b1906e3315c4

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:d16883e193119aad55a98f2535662c6cb72f19b04547f84dba97f35d6cb7d273

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:a5c4731ad9b37b046b7662ef2c0d1cd4259c10b666926d039cee47715ca22929

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=sha256:18bbb9e1bbcfc2071dcac3fdb7cc33e43faec7de65f15ec2890fe1fe8deeece5