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Paper Citation Record · LEDGER

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.12687.

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

pith.paper-citation-record.v1
2608.12687 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:40:02.837446Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

34 of 34 outbound references displayed

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  • verified fuzzy20
  • unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f1295eb1-9ce1-4cd1-8e36-70739ae34ebf · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 1

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Observation e86b7a74-aa9e-4100-b6a8-ad3927b626a6 · outbound

This paper cites ATOM: An automatic topology synthesis framework for operational amplifiers,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization ATOM: An automatic topology synthesis framework for operational amplifiers,

Reference 2

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Observation a9375b81-f332-4af6-86f6-581844bf8cce · outbound

This paper cites CktGNN: Circuit graph neural network for electronic design automation,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization CktGNN: Circuit graph neural network for electronic design automation,

Reference 3

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Observation c42b0887-5893-4074-8c33-22d941a27f51 · outbound

This paper cites Topology optimization of operational amplifier in continuous space via graph embedding,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Topology optimization of operational amplifier in continuous space via graph embedding,

Reference 4

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Observation 6021a8b8-e175-46bf-a447-51350f6d9544 · outbound

This paper cites AnalogGenie: A generative engine for automatic discovery of analog circuit topologies,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization AnalogGenie: A generative engine for automatic discovery of analog circuit topologies,

Reference 5

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Observation 87971971-a94f-4275-afb9-a439e2cfc011 · outbound

This paper cites Ckt2Vec: Efficient electrical encoding for analog circuit representations in vector space,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Ckt2Vec: Efficient electrical encoding for analog circuit representations in vector space,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1aac9f09-3ace-43af-affd-8295f3942858 · outbound

This paper cites Deep kernel learning,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Deep kernel learning,

Reference 7

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Observation cac19272-44d5-44ca-97d5-c587fa1301ff · outbound

This paper cites Bayesian optimization approach for analog circuit synthesis using neural network,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Bayesian optimization approach for analog circuit synthesis using neural network,

Reference 8

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Observation 83daeddb-fb16-400a-8b06-4cefc3f72e69 · outbound

This paper cites KATO: Knowledge alignment and transfer for transistor sizing of different design and technology,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization KATO: Knowledge alignment and transfer for transistor sizing of different design and technology,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 24eb9725-af53-43c3-8ab0-730ee83ccd1e · outbound

This paper cites Reducing evaluation cost for circuit synthesis using active learning,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Reducing evaluation cost for circuit synthesis using active learning,

Reference 10

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Observation e1e6c06a-f1f2-4d73-8759-72608822aa98 · outbound

This paper cites Can an Actor-Critic Optimization Framework Improve Analog Design?.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Can an Actor-Critic Optimization Framework Improve Analog Design?

Reference 11

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Observation ae3721fb-f61c-4b57-943b-b0a4e80ef05d · outbound

This paper cites The reduction of a graph to canonical form and the algebra which appears therein,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization The reduction of a graph to canonical form and the algebra which appears therein,

Reference 12

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Observation fa21a529-cb1a-4c16-8020-e200b3a33ed5 · outbound

This paper cites INTO- OA: Interpretable topology optimization for operational amplifiers,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization INTO- OA: Interpretable topology optimization for operational amplifiers,

Reference 13

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Observation 17e52b8e-3353-4652-8600-608245d851f9 · outbound

This paper cites Depthgraphnet: Circuit graph isomorphism detection via siamese-graph neural networks,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Depthgraphnet: Circuit graph isomorphism detection via siamese-graph neural networks,

Reference 14

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Observation 859ad181-b567-4a76-afcf-acd7fe9673cc · outbound

This paper cites Efficient global optimiza- tion of expensive black-box functions,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Efficient global optimiza- tion of expensive black-box functions,

Reference 15

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Observation 877213d1-017a-41e7-a5e2-8e43fd7b07b5 · outbound

This paper cites Information-theoretic regret bounds for gaussian process optimization in the bandit setting,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Information-theoretic regret bounds for gaussian process optimization in the bandit setting,

Reference 16

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Observation d249fdfe-4c95-4b8a-b2f0-3bebe0e81ebb · outbound

This paper cites On the likelihood that one unknown probability exceeds another in view of the evidence of two samples,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization On the likelihood that one unknown probability exceeds another in view of the evidence of two samples,

Reference 17

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Observation 0d5fdadc-ec69-489c-a54e-703ac7902cd2 · outbound

This paper cites Input warping for bayesian optimization of non-stationary functions,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Input warping for bayesian optimization of non-stationary functions,

Reference 18

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Observation 0032fe9d-fc67-410b-8d76-8e2b54e494ec · outbound

This paper cites Deep kernel bayesian optimization,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Deep kernel bayesian optimization,

Reference 19

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Observation 258d6b54-b39c-43c6-8f6d-cf6b74d8cf1e · outbound

This paper cites Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization

Reference 20

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Observation 1c74ecdf-6d90-415a-8df8-074566c8481c · outbound

This paper cites Contrastive embedding of structured space for bayesian optimization,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Contrastive embedding of structured space for bayesian optimization,

Reference 21

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Observation 4ce01585-bce0-4d90-8cbe-02fa070313a2 · outbound

This paper cites Learning Representation for Bayesian Optimization with Collision-free Regularization.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Learning Representation for Bayesian Optimization with Collision-free Regularization

Reference 22

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Observation fb1daeb0-a2c6-4f2b-82cb-8e3e4c3043f8 · outbound

This paper cites Advancing bayesian optimization via learning correlated latent space,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Advancing bayesian optimization via learning correlated latent space,

Reference 23

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This paper cites Accelerating bayesian optimization for bio- logical sequence design with denoising autoencoders,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Accelerating bayesian optimization for bio- logical sequence design with denoising autoencoders,

Reference 24

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Deep kernel learning for reac- tion outcome prediction and optimization,

Reference 25

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Directed Acyclic Graph Neural Networks

Reference 26

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This paper cites D-vae: A variational autoencoder for directed acyclic graphs,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization D-vae: A variational autoencoder for directed acyclic graphs,

Reference 27

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Semi-Supervised Classification with Graph Convolutional Networks

Reference 28

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Taking the human out of the loop: A review of bayesian optimization,

Reference 29

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Observation adc0000b-3952-492f-89cb-79e587bd7683 · outbound

This paper cites Kernel interpolation for scalable structured gaussian processes (kiss-gp),.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Kernel interpolation for scalable structured gaussian processes (kiss-gp),

Reference 30

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Observation 0af3f7b9-f8c1-41a9-b5a3-c56573322e9f · outbound

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Stochas- tic variational deep kernel learning,

Reference 31

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Observation f46a59e7-c340-4655-afbd-ad619626ee6d · outbound

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Constant- time predictive distributions for gaussian processes,

Reference 32

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Observation bc5ec227-ff51-4424-a055-52a4fcc95180 · outbound

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Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration,

Reference 33

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d4c0bff8-f9cc-42c3-9a1a-17b370af0b6e · outbound

This paper cites Kernel interpolation for scalable online gaussian processes,.

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization Kernel interpolation for scalable online gaussian processes,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:40:02.837446Z digest=sha256:23854aba8c1a45f13dce8a1f252d6993b36dd1c796ec14df012587cc5ac23de9

Pith citing papers

No inbound Pith citation observations are available.