Paper Citation Record · LEDGER

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.12033.

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

pith.paper-citation-record.v1
2501.12033 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:40:32.747018Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

37 of 37 outbound references displayed

verified exact1
verified fuzzy22
unresolved13
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e00855d-66fe-4c7f-812f-967b510bfe0e · outbound

This paper cites Unleashing ai data center growth through optics,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Unleashing ai data center growth through optics,

Reference 1

Resolution: verified exact; raw_fallback, observed 2026-08-10T17:40:32.972578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0ef0b293-4b4e-46a6-b515-088a06260601 · outbound

This paper cites Infrastructure for large scale ai:.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Infrastructure for large scale ai:

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.507773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6e62d8b-2647-4e95-9b25-f0d2e6e68777 · outbound

This paper cites A survey of reconfigurable optical networks,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation A survey of reconfigurable optical networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.492914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 522b141e-08f1-4d51-8408-9d2a0ff18920 · outbound

This paper cites Toward demand-aware networking: A theory for self-adjusting networks,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Toward demand-aware networking: A theory for self-adjusting networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.477516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a459ecff-c896-4f37-accd-3e4fbe51b40c · outbound

This paper cites Network traffic generation: A survey and methodology,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Network traffic generation: A survey and methodology,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.590922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22c19e1e-bfb4-4a02-b636-31a55e47a83c · outbound

This paper cites High-fidelity cellu- lar network control-plane traffic generation without domain knowledge,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation High-fidelity cellu- lar network control-plane traffic generation without domain knowledge,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.452731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f21adb40-a4fc-4c93-83d5-166e436cce25 · outbound

This paper cites Survey of reconfigurable data center net- works: Enablers, algorithms, complexity,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Survey of reconfigurable data center net- works: Enablers, algorithms, complexity,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.438475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9b2fd2c1-0d1d-4424-8540-98fa59686405 · outbound

This paper cites On the complexity of traffic traces and implications,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation On the complexity of traffic traces and implications,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.422906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6e1b0c59-9108-494b-a7d5-7db1438566bd · outbound

This paper cites Projector: Agile reconfigurable data center interconnect,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Projector: Agile reconfigurable data center interconnect,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.406358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0165aac8-c17e-4634-b1f2-7a0eecd46a23 · outbound

This paper cites Demand-aware network designs of bounded degree,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Demand-aware network designs of bounded degree,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.389638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dd5b6496-3a17-476f-9fb2-e1beefbb4801 · outbound

This paper cites Legal issues surrounding monitoring during network research,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Legal issues surrounding monitoring during network research,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.374090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c79c5089-08c8-41e8-956e-e89747a81c9f · outbound

This paper cites Pac-gan: Packet generation of network traffic using gen- erative adversarial networks,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Pac-gan: Packet generation of network traffic using gen- erative adversarial networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.358512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f5377ee9-139f-4d5a-8ca8-fc1a4af927fd · outbound

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

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Practical gan-based synthetic ip header trace generation using netshare,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.343224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 56b8e880-7f0b-4cc3-ac0b-42b5d7f46d77 · outbound

This paper cites Generative spatiotemporal image exploitation for datacenter traffic prediction,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Generative spatiotemporal image exploitation for datacenter traffic prediction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.327945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14a24663-7662-4ad6-afac-38850604f2a7 · outbound

This paper cites Flow-based network traffic generation using generative adversarial networks,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Flow-based network traffic generation using generative adversarial networks,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.638459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87a7f48a-759a-44f6-afc6-e38304bb0c54 · outbound

This paper cites NetGPT: Generative Pretrained Transformer for Network Traffic.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation NetGPT: Generative Pretrained Transformer for Network Traffic

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.642903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f88ff9e-1c86-4722-8c55-cfe2fd589a1e · outbound

This paper cites TrafficGPT: Breaking the Token Barrier for Efficient Long Traffic Analysis and Generation.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation TrafficGPT: Breaking the Token Barrier for Efficient Long Traffic Analysis and Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.647842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27220954-5e61-4935-9f3c-a73c0205341a · outbound

This paper cites Attention is all you need,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Attention is all you need,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.652690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 900b6ee1-8e79-4d9c-810c-9ba65f221589 · outbound

This paper cites Beyond matchings: Dynamic multi- hop topology for demand-aware datacenters,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Beyond matchings: Dynamic multi- hop topology for demand-aware datacenters,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.293645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 22d0f2d5-ee27-42d2-a7f0-8e2793ee38fd · outbound

This paper cites On- line dynamic b-matching: With applications to reconfigurable datacenter networks,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation On- line dynamic b-matching: With applications to reconfigurable datacenter networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.278308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8cb3b959-65aa-48ee-a357-703c909f6d41 · outbound

This paper cites Characterization of the DOE mini-apps,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Characterization of the DOE mini-apps,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.263035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f75b80e-a9d5-4001-a91f-ee64ce5e381f · outbound

This paper cites A mathematical theory of communication,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation A mathematical theory of communication,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.671102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 308bc95b-3030-4761-a31e-c12f6fa18306 · outbound

This paper cites On the complexity of finite sequences,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation On the complexity of finite sequences,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.238848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf55b99e-252c-4330-9cf0-c945b71dabf8 · outbound

This paper cites Universal prediction of indi- vidual sequences,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Universal prediction of indi- vidual sequences,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.223630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f3499d5e-668b-40f3-bab9-a3ed7f45ff43 · outbound

This paper cites Language models are unsupervised multitask learners,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Language models are unsupervised multitask learners,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.684259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6630673-0277-49aa-99af-c495a6d2b2ae · outbound

This paper cites Improving language understanding by generative pre- training,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Improving language understanding by generative pre- training,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.693003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 806fb42d-12aa-4a70-800c-7b6882c8d322 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.699945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a28592d-bea0-46db-9991-5b9420bda84e · outbound

This paper cites Language mod- els are few-shot learners,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Language mod- els are few-shot learners,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.704962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc35901d-57d0-4641-bbeb-a9c6deb07304 · outbound

This paper cites Inside the social network’s (datacenter) network,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Inside the social network’s (datacenter) network,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.178650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3b4b1a96-77ce-4e14-82a3-9a936ade9d72 · outbound

This paper cites COLLECTION, https://trace-collection.net/.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation COLLECTION, https://trace-collection.net/

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.162474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 249b3771-6e27-47b1-982f-4ccc26a52898 · outbound

This paper cites Automated assistance for creative writing with an rnn language model,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Automated assistance for creative writing with an rnn language model,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.146228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 453b9a62-e3a3-4603-8a1e-7dbd928d9415 · outbound

This paper cites Is Temperature the Creativity Parameter of Large Language Models?.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Is Temperature the Creativity Parameter of Large Language Models?

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.723787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f09181f-64fc-4fb7-ae12-a8c5474c5c71 · outbound

This paper cites A learning algorithm for boltzmann machines,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation A learning algorithm for boltzmann machines,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.728297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05f81e78-cd76-42fe-8cb3-4c13cdac1b23 · outbound

This paper cites High-resolution measurement of data center microbursts,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation High-resolution measurement of data center microbursts,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.119585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a4f89a79-a621-471b-a33c-5434bd5db4dd · outbound

This paper cites an unresolved cited work.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Unresolved cited work

Reference 35

Resolution: malformed identifier; doi_truncated, observed 2026-08-10T17:40:32.784977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8309227-822e-4fca-a08c-aced974f9701 · outbound

This paper cites How much do language models copy from their training data? eval- uating linguistic novelty in text generation using raven,.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation How much do language models copy from their training data? eval- uating linguistic novelty in text generation using raven,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:40:33.103783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 21a5fb30-bbee-43da-b678-f24816924e75 · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Quantifying Memorization Across Neural Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T17:40:32.747018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.