Paper Citation Record · LEDGER

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time

As of 14 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2412.15519.

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

pith.paper-citation-record.v1
2412.15519 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:24:37.856882Z

measured 51 of 51 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

51 of 51 outbound references displayed

verified exact1
verified fuzzy3
unresolved45
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5ad567e-9e4b-41ed-b544-92684004baae · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.848195Z

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.

Observation 0a6105a4-3925-46ed-a3bb-4eb93b7bc245 · outbound

This paper cites Language Models are Few-Shot Learners.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Language Models are Few-Shot Learners

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.596526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9f2a6d2-df40-4e6e-aba0-08ee5e997af3 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.831115Z

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.

Observation e77232e3-451e-4e66-99b4-13b1df3631d5 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.607348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bf7618a-53a2-48ad-b885-9e4e889b8845 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.802320Z

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.

Observation 22309182-8a21-4adc-8bff-bfeb86544483 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.782781Z

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.

Observation 6492f627-2e85-4531-9142-cf50130cbad3 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.763562Z

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.

Observation c26afc77-a4f4-4fbe-ae28-5b9d957f17f9 · outbound

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

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.633722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ce28edc-8c16-4f8b-be60-59b9ade65822 · outbound

This paper cites AutoHAS: Efficient Hyperparameter and Architecture Search.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time AutoHAS: Efficient Hyperparameter and Architecture Search

Reference 9

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Source-reported events for the cited work

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

Observation a8bc2276-0552-4125-8524-5bedc52af93e · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.746370Z

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.

Observation ae642ddb-0753-4b43-8dbe-4f29ac6309b5 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.728350Z

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.

Observation 96170166-4656-41a0-921c-a1439f5a38b5 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.712740Z

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.

Observation 02e34f76-0ee1-4b32-aa57-dc434b8f9015 · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Sequence Transduction with Recurrent Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.660109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2e19780-6068-4d9d-adc2-8d061a0c6f3a · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.696479Z

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.

Observation 2e9ff8a1-669e-4101-91f5-97c6e3dbce9d · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 15

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T11:24:38.678197Z

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.

Observation 53f0f577-54cd-434a-a24c-5072de1f8e16 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.676576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fdd4c07-e461-4fcd-b363-9d43d4758816 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.660463Z

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.

Observation 2d4d4aa8-a3f1-4eb3-9d4c-5e29fbed5fd1 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.644212Z

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.

Observation 2ee64ce9-c1e7-42aa-b045-c4ef0612c9eb · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.612279Z

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.

Observation 01e0fe3b-d2ec-498b-a475-2c84c0dfa61c · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.596477Z

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.

Observation 8d6a0cd8-0650-4b43-95da-24afe12d050d · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.580459Z

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.

Observation b85286fc-76c0-46f1-a071-6bffa78f5b25 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Efficient Estimation of Word Representations in Vector Space

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.713673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13da5439-b14f-4331-a029-51e634ac8aee · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.562551Z

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.

Observation 8cc03a5e-a68c-4043-b471-9d4ed03a9331 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.543625Z

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.

Observation 1cb64c96-4ff6-4f76-9a4a-cce479af05df · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.526476Z

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.

Observation 6fdfa873-dea5-41c9-b647-0cf4b6a5dd33 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.509818Z

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.

Observation 5cbfb965-6f58-4c20-8e03-3bc0f47f0077 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.493759Z

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.

Observation a4aab9a9-078f-4a23-a72a-2b15c3987569 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.477009Z

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.

Observation 445938a5-460b-471e-860e-3c82903de518 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.460182Z

Source-reported events for the cited work

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Observation 27b838bf-659e-4a1b-b79a-47d4868402ef · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.444172Z

Source-reported events for the cited work

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Observation d73b50a6-c0a7-4751-b472-26a4e66cd3fe · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.426628Z

Source-reported events for the cited work

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Observation fe4847e6-c6f1-4573-b6b2-ff2654375102 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 32

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Source-reported events for the cited work

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Observation bfb46aa4-f873-41ed-9ae0-0215d12be3fd · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation ec7cc006-d5c5-4b1b-9a6c-f3259053b08a · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 34

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Source-reported events for the cited work

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Observation fa730de3-afcf-4ee5-a3f8-1b23aa034492 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 35

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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.

Observation 53eae451-b95a-4ca5-bca0-5461a5b5505e · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.310426Z

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.

Observation f3e3b662-3151-40de-84ca-5af5a4bc9745 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.291412Z

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.

Observation 93100d48-2888-442b-99bc-e13dff480143 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef1dfbd4-f00a-4f63-98b0-fb874263fe21 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.816770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa4539a6-35c9-4c8f-852e-606b549e4500 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.273673Z

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.

Observation af9a6469-ec78-424a-a0ee-60e7b8706e82 · outbound

This paper cites Sequence to Sequence Learning with Neural Networks.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Sequence to Sequence Learning with Neural Networks

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.827684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5023f356-ddf6-4370-b858-3998de891906 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 514df3c0-ade6-4afa-9935-1a79f01c79ee · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 43

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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.

Observation 56b9ea35-7dd6-4320-8081-6bcf0f3c6148 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.843100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e979f4c9-c73e-4a12-90d7-e92aaf602e08 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.233317Z

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.

Observation 83a3e8a0-1581-4395-8245-c29b68b1bab2 · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.216681Z

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.

Observation 39c54f3c-b69b-4a90-871d-bbe236e01dce · outbound

This paper cites an unresolved cited work.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:24:38.200133Z

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.

Observation 41439d59-6dac-43e5-a73f-65a829534aca · outbound

This paper cites In Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation , Dekai Wu, Marine Carpuat, Xavier Carreras, and Eva Maria Vecchi (Eds.).

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time In Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation , Dekai Wu, Marine Carpuat, Xavier Carreras, and Eva Maria Vecchi (Eds.)

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:37.612515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 184a74b2-c494-4ca0-87c4-aa4957e7aa1f · outbound

This paper cites In 2018 IEEE international conference on big data (Big Data).

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time In 2018 IEEE international conference on big data (Big Data)

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:38.628657Z

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.

Observation a1d704b3-375a-41e1-96e2-7e86a375b1c0 · outbound

This paper cites IEEE Transactions on Parallel and Distributed Systems 32, 8 (2021), 1947–1960.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time IEEE Transactions on Parallel and Distributed Systems 32, 8 (2021), 1947–1960

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:38.380639Z

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.

Observation 36a04676-7ecf-40e4-acd4-dfd767dfbb31 · outbound

This paper cites In Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering.

PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time In Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:24:38.345909Z

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.

Pith citing papers

No inbound Pith citation observations are available.