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Paper Citation Record · LEDGER

Concept-Based Unsupervised Domain Adaptation

As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 3 inbound Pith citation observations for arXiv:2505.05195.

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

pith.paper-citation-record.v1
2505.05195 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:17:03.982645Z

measured 47 of 47 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:11:23.925084Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T06:16:43.870622Z

Reference resolution

44 of 44 outbound references displayed

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  • verified fuzzy15
  • unresolved29
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a516b4a-1b35-47ec-9e8f-743aa16f4541 · outbound

This paper cites write newline.

Concept-Based Unsupervised Domain Adaptation write newline

Reference 1

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Observation f7259f81-12c0-46f1-b501-f9e90c3a04ab · outbound

This paper cites Meaningfully debugging model mistakes using conceptual counterfactual explanations.

Concept-Based Unsupervised Domain Adaptation Meaningfully debugging model mistakes using conceptual counterfactual explanations

Reference 2

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Observation 89da49ed-bcc1-4962-b989-0d3a305914a4 · outbound

This paper cites GPT-4 Technical Report.

Concept-Based Unsupervised Domain Adaptation GPT-4 Technical Report

Reference 3

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Observation 4546e027-8e27-41bf-aa51-a7bd7b03d48a · outbound

This paper cites Domain Adaptations for Computer Vision Applications.

Concept-Based Unsupervised Domain Adaptation Domain Adaptations for Computer Vision Applications

Reference 4

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Observation 68631ac8-950f-42d9-99c9-92c32bd7720a · outbound

This paper cites Analysis of representations for domain adaptation.

Concept-Based Unsupervised Domain Adaptation Analysis of representations for domain adaptation

Reference 5

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Observation b69f9b33-efec-49c0-8523-765699d133b4 · outbound

This paper cites an unresolved cited work.

Concept-Based Unsupervised Domain Adaptation Unresolved cited work

Reference 6

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Observation 5e36b8a8-03ba-436f-a086-24266548c043 · outbound

This paper cites Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts.

Concept-Based Unsupervised Domain Adaptation Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Reference 7

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Observation 7569331d-171a-43b6-9407-f6fc3154e262 · outbound

This paper cites A., Jenkins, M., Liang, W., Rotemberg, V., Ko, J., Swetter, S.

Concept-Based Unsupervised Domain Adaptation A., Jenkins, M., Liang, W., Rotemberg, V., Ko, J., Swetter, S

Reference 8

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Observation 7c3bedaa-9579-47fc-990e-237b10b54d75 · outbound

This paper cites R., Novoa, R., and Zou, J.

Concept-Based Unsupervised Domain Adaptation R., Novoa, R., and Zou, J

Reference 9

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Observation 6ea52dbe-c41f-4f60-af63-a79c2ce2291c · outbound

This paper cites Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning.

Concept-Based Unsupervised Domain Adaptation Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning

Reference 10

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Observation 15bd72e4-d582-4575-bb63-83c25a3cc318 · outbound

This paper cites Domain-adversarial training of neural networks.

Concept-Based Unsupervised Domain Adaptation Domain-adversarial training of neural networks

Reference 11

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Observation d42f986b-410e-4f1a-a9dc-4c8eb2cc9270 · outbound

This paper cites Y., and Kim, B.

Concept-Based Unsupervised Domain Adaptation Y., and Kim, B

Reference 12

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Observation 5bb77fce-fc35-4e33-96f1-df86b99453ae · outbound

This paper cites Generative adversarial nets.

Concept-Based Unsupervised Domain Adaptation Generative adversarial nets

Reference 13

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Observation 8c459656-d2e2-49b9-9377-eeda768670bb · outbound

This paper cites Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset.

Concept-Based Unsupervised Domain Adaptation Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset

Reference 14

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Source-reported events for the cited work

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Observation 9d091d91-49b3-4e81-9356-aaca6c270bd2 · outbound

This paper cites Deep residual learning for image recognition.

Concept-Based Unsupervised Domain Adaptation Deep residual learning for image recognition

Reference 15

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Observation 0c966e60-c0b4-4a48-88d4-530f392ce43a · outbound

This paper cites Cycada: Cycle-consistent adversarial domain adaptation.

Concept-Based Unsupervised Domain Adaptation Cycada: Cycle-consistent adversarial domain adaptation

Reference 16

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Observation 095008e5-158a-4848-9d90-a3f7984a5a78 · outbound

This paper cites Learning unbiased transferability for domain adaptation by uncertainty modeling.

Concept-Based Unsupervised Domain Adaptation Learning unbiased transferability for domain adaptation by uncertainty modeling

Reference 17

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Observation 689082c4-69fc-4e5e-a55f-d6254a927666 · outbound

This paper cites Gradient harmonization in unsupervised domain adaptation.

Concept-Based Unsupervised Domain Adaptation Gradient harmonization in unsupervised domain adaptation

Reference 18

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Source-reported events for the cited work

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Observation 2fcbc91b-e877-4f73-9d2e-fb0a801d2182 · outbound

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Concept-Based Unsupervised Domain Adaptation Unresolved cited work

Reference 19

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Observation 45ae76e4-8e47-4315-af5b-86652bcb80ad · outbound

This paper cites Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav).

Concept-Based Unsupervised Domain Adaptation Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav)

Reference 20

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Observation b2ed1e65-8747-4227-99fd-e58d4113f835 · outbound

This paper cites W., Nguyen, T., Tang, Y.

Concept-Based Unsupervised Domain Adaptation W., Nguyen, T., Tang, Y

Reference 21

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Observation 5aee56ec-1dfc-4bc0-9bcc-f985da278d19 · outbound

This paper cites Gradient-based learning applied to document recognition.

Concept-Based Unsupervised Domain Adaptation Gradient-based learning applied to document recognition

Reference 22

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Observation 3b3bf7e1-5f71-42d0-bc00-6311b29209de · outbound

This paper cites Learning transferable features with deep adaptation networks.

Concept-Based Unsupervised Domain Adaptation Learning transferable features with deep adaptation networks

Reference 23

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Observation ebce3477-3122-43ca-a7bc-b5272b4f0862 · outbound

This paper cites Promises and Pitfalls of Black-Box Concept Learning Models.

Concept-Based Unsupervised Domain Adaptation Promises and Pitfalls of Black-Box Concept Learning Models

Reference 24

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Observation 34574d66-6587-4e80-890b-5bd29f2f6e6e · outbound

This paper cites Y., et al.

Concept-Based Unsupervised Domain Adaptation Y., et al

Reference 25

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Observation db6e0967-e858-447f-8901-830300b4650e · outbound

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Concept-Based Unsupervised Domain Adaptation Unresolved cited work

Reference 26

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Observation fc5ef5c3-7918-4106-8937-61d3234d0dd6 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Concept-Based Unsupervised Domain Adaptation W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 27

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Observation 9dc739fa-4728-4dd3-8c8c-1d61135db1ee · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

Concept-Based Unsupervised Domain Adaptation Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 28

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Observation f4a8dfa0-a842-4186-91a2-7d1936fd82d3 · outbound

This paper cites Maximum classifier discrepancy for unsupervised domain adaptation.

Concept-Based Unsupervised Domain Adaptation Maximum classifier discrepancy for unsupervised domain adaptation

Reference 29

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Observation 636013e5-5c21-4084-a30e-845e646e179a · outbound

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Concept-Based Unsupervised Domain Adaptation D., and Chellappa, R

Reference 30

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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 84a936fd-cf94-47f8-afd4-2b9858358c43 · outbound

This paper cites Wasserstein distance guided representation learning for domain adaptation.

Concept-Based Unsupervised Domain Adaptation Wasserstein distance guided representation learning for domain adaptation

Reference 31

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Observation 126df4b6-616b-4af8-a96e-c171e663e281 · outbound

This paper cites Conceptnet 5.5: An open multilingual graph of general knowledge.

Concept-Based Unsupervised Domain Adaptation Conceptnet 5.5: An open multilingual graph of general knowledge

Reference 32

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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 3afaf53f-19f1-4397-8b40-41005abe6f18 · outbound

This paper cites Unsupervised domain adaptation via structurally regularized deep clustering.

Concept-Based Unsupervised Domain Adaptation Unsupervised domain adaptation via structurally regularized deep clustering

Reference 33

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Observation 2f3d482f-e48c-470d-bfd7-ec981d224b75 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Concept-Based Unsupervised Domain Adaptation The caltech-ucsd birds-200-2011 dataset

Reference 34

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Observation e4ab77a9-983e-47f4-a26f-546616cc47e3 · outbound

This paper cites Continuously indexed domain adaptation.

Concept-Based Unsupervised Domain Adaptation Continuously indexed domain adaptation

Reference 35

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Source-reported events for the cited work

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

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Observation 7d7305e4-920e-4204-b3da-2f7f3d3be1d7 · outbound

This paper cites Discover and cure: Concept-aware mitigation of spurious correlation.

Concept-Based Unsupervised Domain Adaptation Discover and cure: Concept-aware mitigation of spurious correlation

Reference 36

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Observation 36164224-367b-4902-b2a4-a995eaa50617 · outbound

This paper cites Adversarial domain adaptation with domain mixup.

Concept-Based Unsupervised Domain Adaptation Adversarial domain adaptation with domain mixup

Reference 37

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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 8a647778-7c93-4e28-b684-54b9aa8c26be · outbound

This paper cites Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations.

Concept-Based Unsupervised Domain Adaptation Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations

Reference 38

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Observation 44dd96e3-bb4b-472d-9ca5-cc0c734d4f92 · outbound

This paper cites Post-hoc Concept Bottleneck Models.

Concept-Based Unsupervised Domain Adaptation Post-hoc Concept Bottleneck Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:03.963834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:17:03.963834Z digest=sha256:e3b3494bc86e6d2b1d5c43471f2a3b990a195c99c536528828aca80e3ce80a1a

Observation 3ca983d9-f9b6-4663-bb6b-c58b23e693fd · outbound

This paper cites Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off.

Concept-Based Unsupervised Domain Adaptation Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:03.967804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:17:03.967804Z digest=sha256:44e821267388c285dc40f8ac210195a750c32967e86f6d29e34b7f5f78a44416

Observation bb15a89b-249e-482a-92e4-8917d2b283be · outbound

This paper cites Bridging theory and algorithm for domain adaptation.

Concept-Based Unsupervised Domain Adaptation Bridging theory and algorithm for domain adaptation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:04.169611Z

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=arxiv_source observed=2026-08-15T23:17:03.971503Z digest=sha256:9ed38a4b474b5f034a333f752f2715226018c08e2f2826cae8a17365f5389c27

Observation f47392aa-dedf-4955-8747-9700cbab131d · outbound

This paper cites Domain-symmetric networks for adversarial domain adaptation.

Concept-Based Unsupervised Domain Adaptation Domain-symmetric networks for adversarial domain adaptation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:04.157528Z

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=arxiv_source observed=2026-08-15T23:17:03.974930Z digest=sha256:e389f50556ee960530cdbb30c40e048c04e21e57cb8fad03662212466d94c888

Observation b91d1e67-85db-45b9-a6d8-90e477d934b2 · outbound

This paper cites Unsupervised multi-class domain adaptation: Theory, algorithms, and practice.

Concept-Based Unsupervised Domain Adaptation Unsupervised multi-class domain adaptation: Theory, algorithms, and practice

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:03.978336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:17:03.978336Z digest=sha256:c3834a58ca2203c4a1ffa913b5ff7646a663e18902aa2d29a9c8361954057f78

Observation 9eb481a7-8ec9-45bc-83ff-a11c520071eb · outbound

This paper cites S., and Bianchi, M.

Concept-Based Unsupervised Domain Adaptation S., and Bianchi, M

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:04.136235Z

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=arxiv_source observed=2026-08-15T23:17:03.982645Z digest=sha256:b8bd12133dd6ec9f59b7ff15436e0c9b73aa6101d8037cbde47d530d6ede90e7

Pith citing papers

Observation 2efb628c-dde8-40fc-a857-019675fc6dcd · inbound

Matryoshka Concept Bottleneck Models cites this paper.

Matryoshka Concept Bottleneck Models Concept-Based Unsupervised Domain Adaptation

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:04:57.936070Z

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=2026-06-30T18:02:47.654185Z digest=sha256:480721d5f9a51940dc1a5a5eefa833c410e32de63b49b48b32ac4ac6ca727386

Observation 8134b4b2-c14e-4ad3-8c9b-3462b7d63b7e · inbound

Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models cites this paper.

Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models Concept-Based Unsupervised Domain Adaptation

Reference 95

Resolution
verified exact
arxiv_id, observed 2026-07-02T06:16:43.871995Z

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=2026-06-28T07:27:56.163337Z digest=sha256:0f2e84db5badc0ac35eb139de7599867fbfc339b454b70a5f804d8f95ae6f68f

Observation 9feae2ba-19f3-4476-a840-7f31862e7ef3 · inbound

Open-Linguistic Concept Unified Learning for Cross-Site Interpretable Dermatology Image Diagnosis cites this paper.

Open-Linguistic Concept Unified Learning for Cross-Site Interpretable Dermatology Image Diagnosis Concept-Based Unsupervised Domain Adaptation

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T23:11:23.925084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:11:23.925084Z digest=sha256:fbf78b2a2d7fddb0fd7304aefb7bd61b8492f3f3ab048dddf25ecc353266947b