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Paper Citation Record · LEDGER

Born Again Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1805.04770.

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

pith.paper-citation-record.v1
1805.04770 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:18:28.165168Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:47:18.810007Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a3521ded-e457-4c4d-95c5-acf3ef6b207a · inbound

Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning cites this paper.

Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Born Again Neural Networks

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-25T01:30:10.666336Z

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=2026-05-25T01:29:49.752455Z digest=sha256:c9c0ed7d9dd4255e9df4e77e479cc77e22e678d1301afd446b80a0455677a780

Observation d8f169bc-de31-4c7e-8bc3-406379e92572 · inbound

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed cites this paper.

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed Born Again Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-17T03:56:19.931817Z

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=2026-05-17T03:56:19.837017Z digest=sha256:da832a6121090b782fe70c37020a62f6b6914cb9ae74d8eadc1148f26b553475

Observation 58d771da-65c8-4882-be9a-d22d7c73d208 · inbound

Smooth-Distill: A Self-distillation Framework for Multitask Learning with Wearable Sensor Data cites this paper.

Smooth-Distill: A Self-distillation Framework for Multitask Learning with Wearable Sensor Data Born Again Neural Networks

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:28.165168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:28.165168Z digest=sha256:b3fe0a4de0862db08ab4c407c50584cd9eba4cd2fe8a087fbe03e24d3e8a8c75

Observation 0648e23b-f653-4be6-b3c1-e4613c3559fc · inbound

How Should We Meta-Learn Reinforcement Learning Algorithms? cites this paper.

How Should We Meta-Learn Reinforcement Learning Algorithms? Born Again Neural Networks

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T14:48:46.904574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:48:46.904574Z digest=sha256:d70991e161e1f680e494071b7aab9b71e69d008a69a844f68508021867a1e6e3

Observation 4a6e226e-7961-44a7-8eab-3abf36c7c6d6 · inbound

q0: Primitives for Hyper-Epoch Pretraining cites this paper.

q0: Primitives for Hyper-Epoch Pretraining Born Again Neural Networks

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:16:26.595693Z

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=2026-06-28T11:07:20.239027Z digest=sha256:51eb0e0164d9435abcb1b279078126d5a83179cfbdca9bc4ecfb13ea80156e6e

Observation 01f8ddcd-9c39-441b-a4b6-84543ece9fc8 · inbound

TallyTrain: Communication-Efficient Federated Distillation cites this paper.

TallyTrain: Communication-Efficient Federated Distillation Born Again Neural Networks

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T19:47:18.811669Z

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=arxiv_source observed=2026-07-02T19:44:47.733008Z digest=sha256:46b3633866f0da389f121a16915e79e0834c213e419ca39974de4a995baf44a0

Observation 6e3bffac-286c-4cf0-92e7-54ef63efebf1 · inbound

Optimal Self-Distillation for Rectified Flow via Linear Probing cites this paper.

Optimal Self-Distillation for Rectified Flow via Linear Probing Born Again Neural Networks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-02T00:41:47.450288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:41:47.450288Z digest=sha256:bcfebf4345327ee268abbed2fdb171ce1c5f9f8e682cb0230f0f3ff173f6aa4d