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Paper Citation Record · LEDGER

Distributed Collaborative Inference System in Next-Generation Networks and Communication

As of 14 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2412.12102.

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

pith.paper-citation-record.v1
2412.12102 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:23:09.717561Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

32 of 32 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 222e1bb3-a292-46dd-82f7-1ed87d13e354 · outbound

This paper cites Cocktail: A multidimensional optimization for model serving in cloud,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Cocktail: A multidimensional optimization for model serving in cloud,

Reference 1

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5f6d3c22-b436-480c-9ba4-5858a821d9ad · outbound

This paper cites Tabi: An efficient multi- level inference system for large language models,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Tabi: An efficient multi- level inference system for large language models,

Reference 2

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Observation df2177e7-a88c-4770-9259-41ad20580f21 · outbound

This paper cites Bert loses patience: Fast and robust inference with early exit,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Bert loses patience: Fast and robust inference with early exit,

Reference 3

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Observation 3a000fd8-6184-4257-95fa-d42a5754022d · outbound

This paper cites Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 4

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Observation 121735a3-d604-4a09-9fd8-dbab05e6f0f3 · outbound

This paper cites Learning layer-skippable inference network,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Learning layer-skippable inference network,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation aa4ee551-2869-411e-a79a-7037e839245f · outbound

This paper cites Neural network ensembles, cross validation, and active learning,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Neural network ensembles, cross validation, and active learning,

Reference 6

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b0fefc68-e4e3-4c28-82bc-ca5d68fa7702 · outbound

This paper cites An empirical evaluation of bagging and boosting,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication An empirical evaluation of bagging and boosting,

Reference 7

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d3816110-45a6-4210-aca9-29dc9fee25a9 · outbound

This paper cites Calibration of Pre-trained Transformers.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Calibration of Pre-trained Transformers

Reference 8

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source=pdf_text observed=2026-08-12T19:23:09.604971Z digest=sha256:f9c3d2e483394cc334053c1cb2b6b7823a0fb3eb735b4029c34090a378b07e7b

Observation 92925e54-4374-4532-bf70-3682dbc9383f · outbound

This paper cites On calibration of modern neural networks,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication On calibration of modern neural networks,

Reference 9

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Observation 90b91b20-5281-4c8d-b9dd-c5a57285b943 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Branchynet: Fast inference via early exiting from deep neural networks,

Reference 10

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Observation 855a398f-fbd2-4b65-b377-556c78613dcc · outbound

This paper cites What Does BERT Look At? An Analysis of BERT's Attention.

Distributed Collaborative Inference System in Next-Generation Networks and Communication What Does BERT Look At? An Analysis of BERT's Attention

Reference 11

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Observation 4fa1a920-a690-4608-9b39-39d430bd767f · outbound

This paper cites Power-bert: Accelerating bert inference via progres- sive word-vector elimination,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Power-bert: Accelerating bert inference via progres- sive word-vector elimination,

Reference 12

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Observation 6b91e0f3-41ef-4791-a3e8-7900a8601b05 · outbound

This paper cites A systematic review of social media- based sentiment analysis: Emerging trends and challenges,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication A systematic review of social media- based sentiment analysis: Emerging trends and challenges,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T19:23:09.629494Z digest=sha256:57d1d50651e4c1868c369c0e2429e73073122680568bba24c8d9791525e97186

Observation 1a605daf-82cb-45c1-af78-ea33b701b202 · outbound

This paper cites A systematic survey on explainable ai applied to fake news detection,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication A systematic survey on explainable ai applied to fake news detection,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 77d1c69d-13e9-4fe0-8db5-a97b473bd89b · outbound

This paper cites A new chatbot for customer service on social media,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication A new chatbot for customer service on social media,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1506a88c-94c1-418c-bb76-25ef409b6d35 · outbound

This paper cites The roadmap to 6g: Ai empowered wireless networks,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication The roadmap to 6g: Ai empowered wireless networks,

Reference 16

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3b6c76f4-64fd-4729-beb6-050c6c104843 · outbound

This paper cites Artificial-intelligence-enabled intelligent 6g networks,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Artificial-intelligence-enabled intelligent 6g networks,

Reference 17

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raw_fallback, observed 2026-08-12T19:23:10.021878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T19:23:09.648039Z digest=sha256:680bd864888404db8701e4e85be235295eb9a9025b94a731b109cd24520567f6

Observation 0d6385ba-86fa-4c78-a9d8-ad1ffae74eeb · outbound

This paper cites Machine learning in business management using customer behavior analysis using 6g technology,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Machine learning in business management using customer behavior analysis using 6g technology,

Reference 18

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f9ece9fa-275c-45d1-af2b-7727b36477a8 · outbound

This paper cites 6G comprehensive intelligence: network operations and optimization based on Large Language Models.

Distributed Collaborative Inference System in Next-Generation Networks and Communication 6G comprehensive intelligence: network operations and optimization based on Large Language Models

Reference 19

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local_arxiv, observed 2026-08-12T19:23:09.762820Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 85f61e43-9292-4e07-a163-c3af0dfccba9 · outbound

This paper cites Flexnn: Efficient and adaptive dnn inference on memory-constrained edge devices,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Flexnn: Efficient and adaptive dnn inference on memory-constrained edge devices,

Reference 20

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation aacd1eb2-89d0-4f9f-b5db-72be6adccd2c · outbound

This paper cites Cmix-nn: Mixed low-precision cnn library for memory-constrained edge devices,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Cmix-nn: Mixed low-precision cnn library for memory-constrained edge devices,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ef892b0e-60e9-46ca-b63f-20d3b3a78c29 · outbound

This paper cites Model-distributed dnn training for memory-constrained edge computing devices,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Model-distributed dnn training for memory-constrained edge computing devices,

Reference 22

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Unavailable: canonical work link unavailable.

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Observation 6d9a840c-fd3d-4627-bc63-475e50f2dd78 · outbound

This paper cites Auto-split: A general framework of collaborative edge-cloud ai,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Auto-split: A general framework of collaborative edge-cloud ai,

Reference 23

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Observation 3728dd0d-0831-4cd6-8ca4-c333f315467c · outbound

This paper cites Edge-cloud polarization and collaboration: A comprehensive survey for ai,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Edge-cloud polarization and collaboration: A comprehensive survey for ai,

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 2039154f-ad84-48da-9ab6-cc53b103aa6f · outbound

This paper cites Deadline-based dynamic resource allocation and provisioning algorithms in fog-cloud environment,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Deadline-based dynamic resource allocation and provisioning algorithms in fog-cloud environment,

Reference 25

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f8595f73-68ab-4bc0-ad37-47492cecdebf · outbound

This paper cites Analytics-as-a-service in a multi-cloud environment through semantically-enabled hierarchical data processing,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Analytics-as-a-service in a multi-cloud environment through semantically-enabled hierarchical data processing,

Reference 26

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raw_fallback, observed 2026-08-12T19:23:09.912039Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T19:23:09.689402Z digest=sha256:feebd1b0fa1c93632e4e5187b6d7322b8c150fd5f2d06e10102a921ef62467ba

Observation a8b44288-a5fa-4ac2-9e79-5777e5a1ba03 · outbound

This paper cites Trends in ai inference energy consumption: Beyond the performance-vs-parameter laws of deep learning,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Trends in ai inference energy consumption: Beyond the performance-vs-parameter laws of deep learning,

Reference 27

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Unavailable: canonical work link unavailable.

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Observation 9b465d48-f23d-46b2-bdae-a895e36bf153 · outbound

This paper cites Green ai,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Green ai,

Reference 28

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Unavailable: canonical work link unavailable.

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Observation 3ffa0ee1-f18d-4087-8883-d3f6fae772b2 · outbound

This paper cites Green ai: Do deep learning frameworks have different costs?.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Green ai: Do deep learning frameworks have different costs?

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-12T19:23:09.876461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation af0e8149-68db-4499-8d50-12aecc1fb3f5 · outbound

This paper cites Fake news detection using machine learning approaches,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Fake news detection using machine learning approaches,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2b73770c-3dd0-4102-ba3e-0f54dbffe288 · outbound

This paper cites Edgeop- timizer: A programmable containerized scheduler of time-critical tasks in kubernetes-based edge-cloud clusters,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Edgeop- timizer: A programmable containerized scheduler of time-critical tasks in kubernetes-based edge-cloud clusters,

Reference 31

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raw_fallback, observed 2026-08-12T19:23:09.845323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T19:23:09.712952Z digest=sha256:9f3d756b7986ee2127837c5d59f8b58840cdc619432bf1d5e422688ed5587184

Observation c44cc8fb-811a-484a-a804-bb638958dcd3 · outbound

This paper cites A socialized learning-based scheduling framework in intricate edge clouds,.

Distributed Collaborative Inference System in Next-Generation Networks and Communication A socialized learning-based scheduling framework in intricate edge clouds,

Reference 32

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raw_fallback, observed 2026-08-12T19:23:09.829219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

No inbound Pith citation observations are available.