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Paper Citation Record · LEDGER

Transfer Learning for Bayesian Optimization: A Survey

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.05927.

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

pith.paper-citation-record.v1
2302.05927 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:46:50.519015Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

18
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cc8d825f-5f93-4a47-939c-94bf9ccf5d42 · inbound

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings cites this paper.

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings Transfer Learning for Bayesian Optimization: A Survey

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T05:46:50.519015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:46:50.519015Z digest=sha256:ed6af90b6943de0a347b8532c6035187219989e0d49e1aa8a31ece9df8ab5dd4

Observation b6e9c1be-d234-46df-865f-c21b24501330 · inbound

Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization? cites this paper.

Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization? Transfer Learning for Bayesian Optimization: A Survey

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T16:51:15.522683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:51:15.522683Z digest=sha256:3212f1e6f7301e8cd33e0e360872d7e5f05528d87e2f3dcd3ef6c26dd0704b2c

Observation 20a845d0-6071-4827-ba40-ac4a30a90b3e · inbound

Efficient Visual Appearance Optimization by Learning from Prior Preferences cites this paper.

Efficient Visual Appearance Optimization by Learning from Prior Preferences Transfer Learning for Bayesian Optimization: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:31.212436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:31.212436Z digest=sha256:6f18f3169fe8962a089179ae39a64a8dc366cfd3fa048a6ea10994ed02f35e45

Observation b41d8c2d-ad9f-47d0-8f0b-6d267811dc44 · inbound

BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH cites this paper.

BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH Transfer Learning for Bayesian Optimization: A Survey

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:50:58.712293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:49:27.948704Z digest=sha256:904e2071e4910ee2cc07ccda3b749d3b5c9dfdf2d34f3e5330112d37e734670c

Observation fe3a06b0-41e6-4c1a-84cc-61a1777cc7bd · inbound

Bayesian Optimization of a Multi-Product Chemical Reactor Using Composite Models and Partial Physics Knowledge cites this paper.

Bayesian Optimization of a Multi-Product Chemical Reactor Using Composite Models and Partial Physics Knowledge Transfer Learning for Bayesian Optimization: A Survey

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-27T18:01:08.444562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T17:55:44.138515Z digest=sha256:3299d5ed5bb6fadd8d6ed827b47310f72c3d01b8e7d69aa62898a19e4b2f3e4d