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Paper Citation Record · LEDGER

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks

As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2507.14155.

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

pith.paper-citation-record.v1
2507.14155 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:14:07.077003Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

  • verified exact0
  • verified fuzzy47
  • unresolved9
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  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9c99daa-f368-4453-a992-b0d43f019b1b · outbound

This paper cites A Secure and Resilient 6G Architecture Vision of the German Flagship Project 6G-ANNA,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A Secure and Resilient 6G Architecture Vision of the German Flagship Project 6G-ANNA,

Reference 1

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Source-reported events for the cited work

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

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Observation eea616ba-7ed5-4d6b-93d3-c4e016186c86 · outbound

This paper cites Framework and overall objectives of the future d evelopment of IMT for 2030 and beyond,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Framework and overall objectives of the future d evelopment of IMT for 2030 and beyond,

Reference 2

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raw_fallback, observed 2026-08-06T20:14:07.970349Z

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

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Observation 51b8b8ba-63a8-4d72-be6b-becbe59e3133 · outbound

This paper cites Multi-Agent Reinforcement Learning for Dynamic R esource Management in 6G in-X Subnetworks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Multi-Agent Reinforcement Learning for Dynamic R esource Management in 6G in-X Subnetworks,

Reference 3

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

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Observation 13de00d0-307a-4d42-be65-652c09850132 · outbound

This paper cites Extreme Communication in 6G: Vision and Challenges for ‘in -X’ Subnetworks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Extreme Communication in 6G: Vision and Challenges for ‘in -X’ Subnetworks,

Reference 4

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raw_fallback, observed 2026-08-06T20:14:07.942139Z

Source-reported events for the cited work

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

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Observation f89eb1b9-3f1d-4c0d-bbbf-3d658bbe5a6a · outbound

This paper cites Towards 6G in-X subnetworks with sub-mill isecond communication cycles and extreme reliability,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Towards 6G in-X subnetworks with sub-mill isecond communication cycles and extreme reliability,

Reference 5

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raw_fallback, observed 2026-08-06T20:14:07.927292Z

Source-reported events for the cited work

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

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Observation 72d1138c-b3e2-4bdb-8088-f0559e16e2b1 · outbound

This paper cites Interference prediction in wireless networks: Stochastic geometry meet s recursive filtering,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Interference prediction in wireless networks: Stochastic geometry meet s recursive filtering,

Reference 6

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.842738Z digest=sha256:e60f034dfcc16524230860d436278989f3fe4bd739db0930048b795665b17c0e

Observation f575a27d-047f-4eb9-b12d-f2ec22f011c2 · outbound

This paper cites Probabilisti c Interference Prediction for Dynamic 6G In-X Sub-Networks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Probabilisti c Interference Prediction for Dynamic 6G In-X Sub-Networks,

Reference 7

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.847832Z digest=sha256:69f5577401c1225bb3a8a967cf6683df97b84d2205e7bc9550c7da1c3bc4e4df

Observation be6ac10f-e7a2-40ea-b51b-f3ba8754dfb7 · outbound

This paper cites Ex- perimental evidence for heavy tailed interference in the Io T,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Ex- perimental evidence for heavy tailed interference in the Io T,

Reference 8

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

source=pdf_text observed=2026-08-06T20:14:06.851807Z digest=sha256:39e2c05cde4a8cdeb11eaa13176762938d7be56645476318f612dd60da5d28e6

Observation 2ea19ab1-d10c-41b0-b809-d324d4b3e507 · outbound

This paper cites A Nonlinear Autoregressive Neural Network for Interference Prediction and Resource Allocation in URLLC Scenarios,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A Nonlinear Autoregressive Neural Network for Interference Prediction and Resource Allocation in URLLC Scenarios,

Reference 9

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.855990Z digest=sha256:e4bf20aabc7c3fc29cb135a06d0225ca417e98cf8e0ff9413e6ca54ea11aad65

Observation 752e29dc-f234-463a-91a3-430653523b7f · outbound

This paper cites Predictive resource allocation for URLLC us ing em- pirical mode decomposition,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Predictive resource allocation for URLLC us ing em- pirical mode decomposition,

Reference 10

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Source-reported events for the cited work

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

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Observation 499bafa3-8c23-487d-a5f1-f52bbed48c0a · outbound

This paper cites Decomposition Based Interference Management Framework for Local 6G Netwo rks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Decomposition Based Interference Management Framework for Local 6G Netwo rks,

Reference 11

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.865968Z digest=sha256:e6420c26f1c55886087b9a4f7b68f43760ce7e9a8bacd34e675943edb7450ffa

Observation 74d8299e-a2bb-4e7f-8b27-16e658ef7315 · outbound

This paper cites Joint Model and Data-Driven Two-Stage Uplink Interference Predi ction in URLLC Scenarios,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Joint Model and Data-Driven Two-Stage Uplink Interference Predi ction in URLLC Scenarios,

Reference 12

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.870872Z digest=sha256:d6902d63e063234ddcf441475bbb09380e65daa81490ed95fe02ed62a894fb53

Observation c9cc4dfb-5f20-4896-9f69-b504f26b379a · outbound

This paper cites A Predictive Interference Management Algorithm for URLLC in Beyond 5G Networks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A Predictive Interference Management Algorithm for URLLC in Beyond 5G Networks,

Reference 13

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.876188Z digest=sha256:69b5d2307cdacd1da977b6878b0547e37480673ede407fe8a0fbab870a1030b5

Observation ca4725c5-cab0-4221-baf0-99c2b976644b · outbound

This paper cites Interference prediction for low-complexity link adaptat ion in beyond 5G ultra-reliable low-latency communications,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Interference prediction for low-complexity link adaptat ion in beyond 5G ultra-reliable low-latency communications,

Reference 14

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.881157Z digest=sha256:1a9df0b879282fe55377541df3a2a715c5d226cb31184b70bb84e8bf6cf6193f

Observation 39c89402-cfb6-403a-9d90-3acaeda2c728 · outbound

This paper cites Mathematical Modelling and Prediction of Interference Power in In-robot Subnetworks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Mathematical Modelling and Prediction of Interference Power in In-robot Subnetworks,

Reference 15

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

source=pdf_text observed=2026-08-06T20:14:06.886469Z digest=sha256:06fd34bf5dadb37e867af4b30205601330fae9dd2e00e4a88c0e50b797862fbc

Observation a0907224-2204-43fd-a6e0-3648743387b0 · outbound

This paper cites Deep learning for probabilistic interference predictions in mmwave netw orks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Deep learning for probabilistic interference predictions in mmwave netw orks,

Reference 16

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

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Observation da551ec1-4519-49bb-84a5-b3326b34c250 · outbound

This paper cites Cooperative Interference Estimation Using LSTM-Based Federated Learn ing for In- X Subnetworks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Cooperative Interference Estimation Using LSTM-Based Federated Learn ing for In- X Subnetworks,

Reference 17

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

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Observation 96a6d020-bb6d-4ecc-b4f7-19c3295719f3 · outbound

This paper cites Interferenc e Prediction in Unconnected In-X Mobile 6G Subnetworks Using a Data-Driv en Approach,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Interferenc e Prediction in Unconnected In-X Mobile 6G Subnetworks Using a Data-Driv en Approach,

Reference 18

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.900130Z digest=sha256:60c28036b609209454fb6b9446cd61352cf6e703dd0e0438db254366449305bb

Observation ba59760c-49d6-40ee-9766-c67de0c107bd · outbound

This paper cites Ultrareliable and low-latency wireless communication: Tail, risk, and scale,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Ultrareliable and low-latency wireless communication: Tail, risk, and scale,

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:06.904850Z digest=sha256:7905972648038790d66f7b8fec23927c43b91383e3cc3b303e68c0786596ddb6

Observation cb7c0d13-7615-49a3-86f2-b8958a8ace11 · outbound

This paper cites Prediction of Rare Channel Conditions using B ayesian Statistics and Extreme V alue Theory,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Prediction of Rare Channel Conditions using B ayesian Statistics and Extreme V alue Theory,

Reference 20

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source=pdf_text observed=2026-08-06T20:14:06.909350Z digest=sha256:2711efecb72bdc659afbb68febd77794d7c1e1d0dfb5834f79c76559abf5de53

Observation ba2bb24a-1eed-4de5-a32c-1c1edd4f0c44 · outbound

This paper cites Ultra-High Reliability by Predictive Interference Management Using Extreme Value Theory.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Ultra-High Reliability by Predictive Interference Management Using Extreme Value Theory

Reference 21

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source=pdf_text observed=2026-08-06T20:14:06.913565Z digest=sha256:80fb9b44fd3f261f9fa7cd2893a6908e6f43f1a5e8ceb6d4736220f0bcc51803

Observation 4621d303-ea64-4d1e-b0ab-9a8e80a2aba0 · outbound

This paper cites Extreme V alu e Theory- based Predictive Interference Management for 6G Subnetwor ks with Transformer,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Extreme V alu e Theory- based Predictive Interference Management for 6G Subnetwor ks with Transformer,

Reference 22

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

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Observation 7e755819-d2fc-471a-93d4-83f39e01cd0b · outbound

This paper cites A 5G Traffic Model for Industrial Use Cases,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A 5G Traffic Model for Industrial Use Cases,

Reference 23

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

source=pdf_text observed=2026-08-06T20:14:06.922553Z digest=sha256:7a7aa01cd8bb852a1edd35d58b215ff2129a7d06c8486112d442923a7b79f805

Observation bbba71e4-de4b-4451-aa8b-70e41c2dfa05 · outbound

This paper cites Advanc ed frequency resource allocation for industrial wireless control in 6G s ubnetworks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Advanc ed frequency resource allocation for industrial wireless control in 6G s ubnetworks,

Reference 24

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

source=pdf_text observed=2026-08-06T20:14:06.926616Z digest=sha256:ffcfef7136c8876a19d8ed39393b6171b540450f6574cbca706c25c57c97dca2

Observation 2d11f161-ce76-443a-ad1d-afbe006f5a15 · outbound

This paper cites Enabling URLLC in 5G NR IIoT networ ks: A full-stack end-to-end analysis,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Enabling URLLC in 5G NR IIoT networ ks: A full-stack end-to-end analysis,

Reference 25

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raw_fallback, observed 2026-08-06T20:14:07.646714Z

Source-reported events for the cited work

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

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Observation c66b3bf3-ed28-4124-8c64-25f74730763c · outbound

This paper cites Distribut ed Scheduling in Multiple Access With Bursty Arrivals Under a Maximum Dela y Constraint,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Distribut ed Scheduling in Multiple Access With Bursty Arrivals Under a Maximum Dela y Constraint,

Reference 26

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raw_fallback, observed 2026-08-06T20:14:07.631569Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.935188Z digest=sha256:0055a128019453b38e6c8e8200901aa20f552fe963387136522f91b1c70721c9

Observation f421ee0a-589b-4ef7-bf0f-e9c062ad34d1 · outbound

This paper cites Service requirements for the 5G system,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Service requirements for the 5G system,

Reference 27

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raw_fallback, observed 2026-08-06T20:14:07.615657Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.939376Z digest=sha256:bdf2faa1c1a24cee6a37a616521110878e515145f2f04fbef463adb718679173

Observation 9eb52695-f76e-4d7d-88a3-88e7433a8165 · outbound

This paper cites Coexistence of Pull and Push Communication in Wireless Access for IoT Devices,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Coexistence of Pull and Push Communication in Wireless Access for IoT Devices,

Reference 28

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raw_fallback, observed 2026-08-06T20:14:07.599419Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.943812Z digest=sha256:589accee33a4bd2faa43e75adc6b60bc44f0f1dcc7be52dfebba1ac6012ed3b2

Observation 1092683d-03b5-441e-9415-19214fe1c02f · outbound

This paper cites Study on communication for automation in vertic al domains (cav),.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Study on communication for automation in vertic al domains (cav),

Reference 29

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raw_fallback, observed 2026-08-06T20:14:07.582485Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.947860Z digest=sha256:d5603c3dbcfc28b9d0d330df0ba7a21de7cd8b894b1a5e1c4c336734c6b4c2b6

Observation 78a263fa-4f1c-4330-b6e8-d0ca5320f836 · outbound

This paper cites Novel sum-of-s inusoids simulation models for Rayleigh and Rician fading channels,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Novel sum-of-s inusoids simulation models for Rayleigh and Rician fading channels,

Reference 30

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raw_fallback, observed 2026-08-06T20:14:07.566180Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.952116Z digest=sha256:75c3d1a86d6990c768c2d75374c28b818d60eee2ab2c1a7f8934d62ae4f031a6

Observation 14d35e69-f514-4239-9dfe-4f68385f928e · outbound

This paper cites 5G: Study on channel model for frequencies from 0 .5 to 100 GHz (3GPP TR 38.901 version 16.1.0 release 16),.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks 5G: Study on channel model for frequencies from 0 .5 to 100 GHz (3GPP TR 38.901 version 16.1.0 release 16),

Reference 31

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raw_fallback, observed 2026-08-06T20:14:07.550812Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.956675Z digest=sha256:14d30d34ef4f70fd2b78e295df02a868d841049577708ac9208be6d290f6a7fb

Observation 1d679eaa-5f8d-4663-b78b-7353a4596f31 · outbound

This paper cites Effects of correlated sh adowing modeling on performance evaluation of wireless sensor netw orks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Effects of correlated sh adowing modeling on performance evaluation of wireless sensor netw orks,

Reference 32

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raw_fallback, observed 2026-08-06T20:14:07.534932Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.961348Z digest=sha256:133fcaa8e04363449cf3b0ef9bf0e072b2ec5863c12859096bd0d2d9c4bbcac7

Observation e484df0e-87a5-4884-a374-00aa4326d004 · outbound

This paper cites Inter- ference data collection with beam information for ml-based interference prediction,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Inter- ference data collection with beam information for ml-based interference prediction,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.520215Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.965582Z digest=sha256:9c09d4081c5ebd3d59c27bcb1db4e64bac49323662a07e939ff7ef6912556507

Observation 47c877b2-9303-4140-9d3e-8e486c7bf470 · outbound

This paper cites Channel coding rate in the finite blocklength regime,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Channel coding rate in the finite blocklength regime,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:06.970039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:06.970039Z digest=sha256:dbc774ab0ddf24a63996220ded46c8c5c3e011749fdcfbec9c631e7b50d676d4

Observation 8d0a22cd-c652-4298-9d61-73e3afb875c5 · outbound

This paper cites Improving QoS by predictive channel quality feedback for LTE,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Improving QoS by predictive channel quality feedback for LTE,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.493876Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.974309Z digest=sha256:d0d902f40909e227f34551a111b92d712c4ab63a646f7ae2e4cff99c6f719528

Observation acd4c513-aae0-41f1-bab3-a49d0616b59f · outbound

This paper cites Correlat ion matrix distance, a meaningful measure for evaluation of non-stati onary MIMO channels,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Correlat ion matrix distance, a meaningful measure for evaluation of non-stati onary MIMO channels,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.475892Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.978935Z digest=sha256:73a235e82c4de549856a9d7ddbf76518730c28ce932ca6dde1280ff79bb5d6df

Observation 81e0c9f2-36d4-4063-ae0c-8a1ddabc622e · outbound

This paper cites E mpirical channel stationarity in urban environments,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks E mpirical channel stationarity in urban environments,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.461089Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.983574Z digest=sha256:19c410b25850a1349d3277a0a953459b27561f54c2381d84c9de71300b37a205

Observation 851d03a8-9c73-46e9-9855-6a2e942477e0 · outbound

This paper cites Distances and Riemannian metrics for s pectral density functions,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Distances and Riemannian metrics for s pectral density functions,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.446131Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.988040Z digest=sha256:f26e12c25df5989298c71322b0b97f658ed51c19fffa222badc1e5157f371a9a

Observation a187bf97-b216-42eb-abd8-f8d900e2d0cf · outbound

This paper cites Prob abilistic individual load forecasting using pinball loss guided LSTM ,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Prob abilistic individual load forecasting using pinball loss guided LSTM ,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.430355Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:06.992686Z digest=sha256:8bfc603c45a3fa029f7f0c5f3d84bf2140f5aba19278a497d6fd20091dbb8892

Observation 0e75856e-a7f7-4f68-a453-39fa27fec327 · outbound

This paper cites Conformalized quantile regression,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Conformalized quantile regression,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:06.997523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:06.997523Z digest=sha256:3204c5e6769ec64803628ab40bebdf5d5f6b5db94a3191cc358781347af0d04c

Observation a9055c3a-c080-48dc-81cf-dd6e40402f17 · outbound

This paper cites V ovk, A.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks V ovk, A

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.404111Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.001917Z digest=sha256:d2a8cecef4bf646aaf88ad1ceb103957060730afb790a3d016638aa758d8437f

Observation cc5f3594-4ec0-4cf3-870b-659e5227dc81 · outbound

This paper cites Conformal prediction for time series,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Conformal prediction for time series,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.389894Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.006878Z digest=sha256:aec805cef205deca5ffea5e60b47f63d30f4bbc1971cfffe6ca3b7af34922ac1

Observation cd015246-1b06-48ac-8c86-2061c6230cf3 · outbound

This paper cites Conf ormal time- series forecasting,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Conf ormal time- series forecasting,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.373614Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.011387Z digest=sha256:9798f77b886ea7551485521659d294187038ea28c7f6e3abeda091a4e402a13d

Observation 02e5996e-693e-43b9-abf5-71a1a0268a50 · outbound

This paper cites A Tutorial on Conformal Predicti on.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A Tutorial on Conformal Predicti on

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.358022Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.015915Z digest=sha256:85cd10959d6c07a50ee75d3d110d5955a435187ebdc5c362e300dc117c24dfee

Observation 9ae939fc-f2ef-4915-9314-0be584f1f2ef · outbound

This paper cites Conformal prediction interval est imation and applications to day-ahead and intraday power markets,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Conformal prediction interval est imation and applications to day-ahead and intraday power markets,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.342693Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.020187Z digest=sha256:e7539e855f234a3157292e8f9136b1666746dd360971b0159f64e824848327bb

Observation 8116c419-d560-4c44-861c-f7932112e222 · outbound

This paper cites Inductive confidence machines for regression,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Inductive confidence machines for regression,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.326941Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.024832Z digest=sha256:f4b193cce02d9337366382dc9f901bbefa3adb8f998934dce1096ce5461b5a05

Observation 4e3d74ec-eebd-455a-afe9-0c29d9ea489b · outbound

This paper cites Ensemble Co nformalized Quantile Regression for Probabilistic Time Series Forecas ting,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Ensemble Co nformalized Quantile Regression for Probabilistic Time Series Forecas ting,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.309742Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.030098Z digest=sha256:ed04513373b6303a0cf158bb912ecd49b73d68fa513b2023fb30283b5d73d428

Observation 7abd2636-f100-4486-bb21-f88edcc2d824 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:07.034185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:07.034185Z digest=sha256:385de3a5e754ea64a7b65759d7af0cb86da72fdca13ed744373e6fbb685a83c2

Observation c0f8f272-aa2b-4adb-9aba-634c578b7484 · outbound

This paper cites A T ime Series is Worth 64 Words: Long-term Forecasting with Transf ormers,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A T ime Series is Worth 64 Words: Long-term Forecasting with Transf ormers,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.293748Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.038962Z digest=sha256:f41dbec9ba2c5244997e45fe19befd8dd2823c99ded6e25982465b975c71511a

Observation 4a64dd70-c9cd-4b0c-b2a9-8997b078d66d · outbound

This paper cites Attention is All you Need,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Attention is All you Need,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.275836Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.043421Z digest=sha256:35585e0accca4d62a3123b8c94fa2e3e4012715a22986ace7852327722dc4a51

Observation 22149d6e-687b-4e0a-b294-05496b9113b5 · outbound

This paper cites R eversible instance normalization for accurate time-series forecast ing against distri- bution shift,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks R eversible instance normalization for accurate time-series forecast ing against distri- bution shift,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.261095Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.048154Z digest=sha256:fe85fde8ecf3e31e94ee95a85a77efe11ff3f0a19466d6f9fe894ca9f02736aa

Observation 6024a4e3-6e90-4eb2-96cc-9411d2a0e54a · outbound

This paper cites an unresolved cited work.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:14:07.245530Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.053187Z digest=sha256:4c02fbb28406816c9936b5f4b981c345a545f58f83d6c5395275b9cab2154dad

Observation 45d10c73-396a-4666-90a8-0214d2369a88 · outbound

This paper cites Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:07.058393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:07.058393Z digest=sha256:762c662eb883f0c59c298268c4ca947e08782246721b64db264347b5575ae7bb

Observation 105d82ec-51e0-436f-a26f-acfc392ab87a · outbound

This paper cites Haan and A.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Haan and A

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.228522Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.063288Z digest=sha256:ecc33860efd0ad989390f23383d0c7a8f14be676c08470f175659c584fab81ad

Observation d073b0d5-d2b2-4362-bec2-c7a7605d07ec · outbound

This paper cites Efficient parallel split learning over resource-constrai ned wireless edge networks,.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Efficient parallel split learning over resource-constrai ned wireless edge networks,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:14:07.209838Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:14:07.067835Z digest=sha256:7d37682e71fcf821748c3c8f460915c5a55945e043982c9331f83768ad8b0192

Observation 0243994d-8025-4088-bf6b-bdd1d2d0265c · outbound

This paper cites A Survey on Activation Functions and their relation with Xavier and He Normal Initialization.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks A Survey on Activation Functions and their relation with Xavier and He Normal Initialization

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:07.072299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:07.072299Z digest=sha256:6be4b1dbcc101c28d0390e3fc4a6259cd5d8d5b37dc80881501bf52f1d8f81ae

Observation 800e026c-c1d6-47d9-a807-f3941340edbe · outbound

This paper cites an unresolved cited work.

Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks Unresolved cited work

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T20:14:07.077003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:14:07.077003Z digest=sha256:a67142a678edc219a11aa07d282730d2eaa3df2e305a8d90d89ebac25ce90285

Pith citing papers

No inbound Pith citation observations are available.