Paper Citation Record · LEDGER

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2508.20089.

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

pith.paper-citation-record.v1
2508.20089 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:17:17.325568Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation 869dc9b1-d5e4-4e6d-81cb-75cff31e195c · outbound

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

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This paper cites Bar-On, Rob Phillips, and Ron Milo.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Bar-On, Rob Phillips, and Ron Milo

Reference 2

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

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This paper cites An automated light trap to monitor moths (lepidoptera) using computer vision-based tracking and deep learning.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors An automated light trap to monitor moths (lepidoptera) using computer vision-based tracking and deep learning

Reference 4

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This paper cites Ob- ject detection of small insects in time-lapse camera record- ings.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Ob- ject detection of small insects in time-lapse camera record- ings

Reference 6

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This paper cites Mann, Toke T.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Mann, Toke T

Reference 7

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

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This paper cites The taxo- nomic impediment: a shortage of taxonomists, not the lack of technical approaches.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors The taxo- nomic impediment: a shortage of taxonomists, not the lack of technical approaches

Reference 9

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This paper cites Gardiner, Sareh Rowlands, and Benno I.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Gardiner, Sareh Rowlands, and Benno I

Reference 10

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This paper cites Wang, Xiaoliang Huo, Joakim B.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Wang, Xiaoliang Huo, Joakim B

Reference 11

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This paper cites Campolongo, Matthew J.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Campolongo, Matthew J

Reference 12

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This paper cites Høye, Johanna ¨Arje, Kim Bjerge, Oskar L.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Høye, Johanna ¨Arje, Kim Bjerge, Oskar L

Reference 13

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This paper cites Insect identification in the wild: The ami dataset.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Insect identification in the wild: The ami dataset

Reference 14

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This paper cites A method to establish a synthetic image dataset of stored-product insects for insect detection.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors A method to establish a synthetic image dataset of stored-product insects for insect detection

Reference 15

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This paper cites Data-Free Knowledge Transfer: A Survey.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Data-Free Knowledge Transfer: A Survey

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors A convnet for the 2020s

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Losey and Mace Vaughan

Reference 18

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Decoupled Weight Decay Regularization

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Montgomery, Michael W

Reference 20

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This paper cites A survey on knowledge distillation: Recent advancements.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors A survey on knowledge distillation: Recent advancements

Reference 21

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This paper cites Insect- foundation: A foundation model and large-scale 1m dataset for visual insect understanding.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Insect- foundation: A foundation model and large-scale 1m dataset for visual insect understanding

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Kalkman, and Dan Stowell

Reference 23

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Learning transferable visual models from natural language supervi- sion

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Motion vectors and deep neural networks for video camera traps

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Insect detect: An open-source diy camera trap for automated insect monitoring

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Thompson, Eliza- beth G

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors The inaturalist species classification and de- tection dataset

Reference 30

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This paper cites Bowler, Konstantin B.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Bowler, Konstantin B

Reference 31

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Towards zero-shot camera trap image categorization

Reference 32

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Wagner, Eliza M

Reference 33

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Deep visual domain adapta- tion: A survey

Reference 34

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This paper cites Deng, Andre Nakkab, Md Zahid Hasan, et al.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Deng, Andre Nakkab, Md Zahid Hasan, et al

Reference 35

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Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Unresolved cited work

Reference 36

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This paper cites Statistics of each domain-mixed training dataset at var- ious amounts of target-domain percentages.

Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors Statistics of each domain-mixed training dataset at var- ious amounts of target-domain percentages

Reference 37

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Pith citing papers

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