Paper Citation Record · LEDGER

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.12074.

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

pith.paper-citation-record.v1
2506.12074 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:28:44.022148Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact2
verified fuzzy25
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 30fad990-02c0-4bb1-a585-c4b85b92bc7d · outbound

This paper cites Heuristic algorithms for RIS-assisted wireless networks: Exploring heuristic-aided machine learning,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Heuristic algorithms for RIS-assisted wireless networks: Exploring heuristic-aided machine learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:49.884870Z

Source-reported events for the cited work

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

Observation 13a93871-de95-47f2-a904-68638293fd06 · outbound

This paper cites Intelligent reflecting surface assisted terahertz communications toward 6G,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Intelligent reflecting surface assisted terahertz communications toward 6G,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:49.629702Z

Source-reported events for the cited work

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

Observation a6d5f7bb-58f3-4a23-bbb6-968ddecd5e69 · outbound

This paper cites The road towards 6G: A comprehensive survey,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection The road towards 6G: A comprehensive survey,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:49.412619Z

Source-reported events for the cited work

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

Observation b66fa307-f512-4b4a-a7e9-8cf21d1fefe8 · outbound

This paper cites Transformer-based wireless traffic prediction and network optimization in O-RAN,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Transformer-based wireless traffic prediction and network optimization in O-RAN,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:49.150347Z

Source-reported events for the cited work

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

Observation ea72956b-c4df-48cf-8e1b-61e0b53a155a · outbound

This paper cites Air traffic and usage predictions in avionic communications using attention based vaegan model,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Air traffic and usage predictions in avionic communications using attention based vaegan model,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:48.904284Z

Source-reported events for the cited work

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

Observation a856f03b-02ac-48d2-ae87-e3b386a63ecb · outbound

This paper cites Weighted moving average forecast model based prediction service broker algorithm for cloud computing,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Weighted moving average forecast model based prediction service broker algorithm for cloud computing,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:48.687152Z

Source-reported events for the cited work

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

Observation 1ebc77c1-79b9-4c49-95ac-278c44b1bfb3 · outbound

This paper cites Dual attention-based federated learning for wireless traffic prediction,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Dual attention-based federated learning for wireless traffic prediction,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:48.465039Z

Source-reported events for the cited work

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

Observation 5adba74c-afe9-4de4-8de2-a3ac89947f20 · outbound

This paper cites RL meets multi-link operation in IEEE 802.11 be: Multi- headed recurrent soft-actor critic-based traffic allocation,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection RL meets multi-link operation in IEEE 802.11 be: Multi- headed recurrent soft-actor critic-based traffic allocation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:48.211210Z

Source-reported events for the cited work

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

Observation 196c376e-720f-4eb1-8a57-341c9eda2ee1 · outbound

This paper cites LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:28:44.588035Z

Source-reported events for the cited work

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

Observation 2b522302-345b-4d18-b1b0-9cfc382cafeb · outbound

This paper cites Cbam: Convolutional block attention module,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Cbam: Convolutional block attention module,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:40.679780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60974a6a-8fa7-49c4-b067-3cd644d770a3 · outbound

This paper cites Efficient multi-scale attention module with cross-spatial learning,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Efficient multi-scale attention module with cross-spatial learning,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:40.743230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f41c6ea-21d5-4eb6-9084-055009b7d65e · outbound

This paper cites Phase shift compression for control signaling reduction in irs-aided wireless systems: Global attention and lightweight design,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Phase shift compression for control signaling reduction in irs-aided wireless systems: Global attention and lightweight design,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:47.871591Z

Source-reported events for the cited work

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

Observation 72126ef2-8659-4957-8601-7038ac2516d7 · outbound

This paper cites One fits all: Power general time series analysis by pretrained LM,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection One fits all: Power general time series analysis by pretrained LM,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:47.650059Z

Source-reported events for the cited work

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

Observation db17b326-78a7-41ed-9c0f-6a45b4fec19f · outbound

This paper cites Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:41.060190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31a5b495-50df-476c-81e1-d6c2b8a8775c · outbound

This paper cites Large language models are zero-shot time series forecasters,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Large language models are zero-shot time series forecasters,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:47.438561Z

Source-reported events for the cited work

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

Observation ca159f0a-cefb-4410-80d1-297921877023 · outbound

This paper cites Large language models can be easily distracted by irrelevant context,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Large language models can be easily distracted by irrelevant context,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:41.278540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f6ef5e2-c8c5-4660-82bf-30395579a5bb · outbound

This paper cites Why larger language models do in-context learning differently?.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Why larger language models do in-context learning differently?

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:47.225039Z

Source-reported events for the cited work

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

Observation f241cf5f-7770-47a0-9fd1-a324f189399a · outbound

This paper cites Beyond throughput, the next generation: A 5G dataset with channel and context metrics,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Beyond throughput, the next generation: A 5G dataset with channel and context metrics,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:47.088858Z

Source-reported events for the cited work

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

Observation 943a32a2-92ae-4996-acd9-714813847c69 · outbound

This paper cites In-Context Learning with Iterative Demonstration Selection.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection In-Context Learning with Iterative Demonstration Selection

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:41.540741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ca61f34-e437-49d2-bdb0-3729010bf890 · outbound

This paper cites Realtime mobile bandwidth and handoff predictions in 4G/5G networks,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Realtime mobile bandwidth and handoff predictions in 4G/5G networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:46.943352Z

Source-reported events for the cited work

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

Observation 427dd286-a5ca-4ef2-9510-b950fc07c38c · outbound

This paper cites A meta-learning scheme for adaptive short-term network traffic prediction,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection A meta-learning scheme for adaptive short-term network traffic prediction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:46.771309Z

Source-reported events for the cited work

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

Observation 9df939e2-bf64-4aca-84b9-46ecf2cfc6df · outbound

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

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Mobile data traffic prediction by exploiting time-evolving user mobility patterns,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:41.761269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a41400c7-7973-49a9-ba3a-579baab34277 · outbound

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

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Mobile traffic prediction from raw data using LSTM networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:46.556383Z

Source-reported events for the cited work

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

Observation dfb96bfb-9ed2-4ec5-b07a-4930e605f778 · outbound

This paper cites ST-Tran: Spatial-temporal transformer for cellular traffic prediction,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection ST-Tran: Spatial-temporal transformer for cellular traffic prediction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:46.382817Z

Source-reported events for the cited work

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

Observation 8595b258-d835-4cbc-bb89-940e5c7fe2a8 · outbound

This paper cites Performance analysis of network traffic predictors in the cloud,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Performance analysis of network traffic predictors in the cloud,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:46.170780Z

Source-reported events for the cited work

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

Observation a8dbecca-cebc-452e-be3f-5e6b52047932 · outbound

This paper cites Network traffic prediction method based on au- toregressive integrated moving average and adaptive volterra filter,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Network traffic prediction method based on au- toregressive integrated moving average and adaptive volterra filter,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:45.928289Z

Source-reported events for the cited work

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

Observation dca585c9-0c93-45da-89b6-ae6114c79f4a · outbound

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

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.267258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aca4bdee-92f2-4b99-a042-a9ed9759b25f · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.341490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 168c51e3-cfbe-4ebb-a91e-13fc9c87bcd4 · outbound

This paper cites Self-refined generative foundation models for wireless traffic prediction,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Self-refined generative foundation models for wireless traffic prediction,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.439715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2623eb22-4401-4727-a93f-cb9711373bd3 · outbound

This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.535713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56fba14b-c21f-4fa6-89ae-d7b9599c605c · outbound

This paper cites Understanding Emergent In-Context Learning from a Kernel Regression Perspective.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Understanding Emergent In-Context Learning from a Kernel Regression Perspective

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.630545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edd0e1ba-d77f-4af3-a532-8769bacd18ec · outbound

This paper cites Why can GPT learn in-context? language models implicitly perform gradient descent as meta-optimizers,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Why can GPT learn in-context? language models implicitly perform gradient descent as meta-optimizers,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:45.700404Z

Source-reported events for the cited work

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

Observation 20c64c64-1063-4123-8313-09a6c4885605 · outbound

This paper cites Learning To Retrieve Prompts for In-Context Learning.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Learning To Retrieve Prompts for In-Context Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:42.847907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2381f08-fd5c-41a4-973b-4cb7d81979bf · outbound

This paper cites What makes good examples for visual in-context learning?.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection What makes good examples for visual in-context learning?

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:45.493795Z

Source-reported events for the cited work

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

Observation 4b3eeca2-6627-4103-81ca-9d7e15f46fa6 · outbound

This paper cites Linkforecast: Cellular link bandwidth prediction in LTE networks,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Linkforecast: Cellular link bandwidth prediction in LTE networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:45.301971Z

Source-reported events for the cited work

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

Observation 42a9c4d4-3a3c-4cbf-9a51-feb7a1130bb4 · outbound

This paper cites Active Example Selection for In-Context Learning.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Active Example Selection for In-Context Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:43.164025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1a4be91-82f6-4956-bade-8312eedbe4d1 · outbound

This paper cites Llm-inference- bench: Inference benchmarking of large language models on ai acceler- ators,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Llm-inference- bench: Inference benchmarking of large language models on ai acceler- ators,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:43.283095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa0e9e2b-1e4a-4c95-b54b-b929e7a7bb38 · outbound

This paper cites Latency-aware joint task offloading and energy control for cooperative mobile edge computing,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Latency-aware joint task offloading and energy control for cooperative mobile edge computing,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:45.117405Z

Source-reported events for the cited work

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

Observation f35ab3db-411f-4ae3-9698-4ff4d821eb53 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:43.465361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1c44c40-420b-4e34-9fe4-9bc2eb4ea36f · outbound

This paper cites Why does in-context learning fail sometimes? Evaluating in-context learning on open and closed questions.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Why does in-context learning fail sometimes? Evaluating in-context learning on open and closed questions

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:28:44.271957Z

Source-reported events for the cited work

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

Observation 3b18aec5-2df5-4169-bd5d-3f3d8a7b3c08 · outbound

This paper cites What makes a good order of examples in in-context learning,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection What makes a good order of examples in in-context learning,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:44.920499Z

Source-reported events for the cited work

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

Observation 305267ee-3ce1-4f34-99ee-39ff0f8abf92 · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:43.802996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5bc7b88-0eb8-4a1d-8514-d6354f3ffd31 · outbound

This paper cites Self-adaptive in-context learning: An information compression perspective for in-context example selec- tion and ordering,.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Self-adaptive in-context learning: An information compression perspective for in-context example selec- tion and ordering,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:28:44.735758Z

Source-reported events for the cited work

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

Observation 2c873d46-6df4-44ea-aad2-6fecb0f5cdd2 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:44.022148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.