Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:26:56.217167Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2607.17653.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:26:56.217167Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
60 of 60 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation bc7ed6d6-f6c9-4dad-9154-b836f88307ab · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Transfer adaptation learning: A decade survey,
Reference 1
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Observation b15582f7-4a3e-45de-bec6-3a559ea4568e · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Enhancing multi-source open-set domain adaptation through nearest neighbor classification with self-supervised vision transformer,
Reference 2
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Observation 3b856c9d-a980-451b-8aaf-5d432a678fc1 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Learning to transfer examples for partial domain adaptation,
Reference 3
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Observation 6ba5cb01-23bd-427f-8ca7-0c1b206be178 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Psdc: A prototype- based shared-dummy classifier model for open-set domain adaptation,
Reference 4
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Observation 789b453d-192d-4cd2-8dce-3331a5ce697b · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Universal domain adaptation,
Reference 5
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Observation e11f0fcd-bd27-4b39-b828-a53a9ffcd8e6 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Universal domain adaptation through self supervision,
Reference 6
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Observation 6f2f4d28-dd75-4122-a8fa-c6c76aa41930 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Geometric anchor correspondence mining with uncertainty modeling for universal domain adaptation,
Reference 7
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Observation c70ca773-8241-4a31-bff3-cac0f785e16b · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation The eu general data protection regu- lation (gdpr),
Reference 8
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Observation c4d1bf40-7abc-4215-b51f-33471a2fa698 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Upcycling models under domain and category shift,
Reference 9
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Observation 06058701-8edb-466f-bcb9-a6dea33d02d1 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Universal domain adaptation via compressive attention matching,
Reference 10
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Observation 51090e1e-158c-449d-b97b-111f662f8d4e · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation UMAD: Universal Model Adaptation under Domain and Category Shift
Reference 11
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Observation 3430aa17-4f57-4da6-93b8-2bae9d7b47b3 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Universal source-free domain adaptation,
Reference 12
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Observation 21dd23d4-c3ca-4ea3-ba28-a6abb81bd0d9 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Learning to detect open classes for universal domain adaptation,
Reference 13
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Observation 9ccf251e-7d38-478b-a0ba-8b9df7558f8f · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Unveiling the unknown: Unleashing the power of unknown to known in open-set source-free domain adaptation,
Reference 14
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Observation 3a0ab51a-089c-4257-98f7-047e24b8ca5a · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Lead: Learning decomposition for source-free universal domain adapta- tion,
Reference 15
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Observation 5a458cf7-00e6-493e-b6e5-be7bcf71e9e7 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Domain invariant and class discriminative feature learning for visual domain adaptation,
Reference 16
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Observation fa9eec10-8139-45bc-96c1-94e3f1f3f00a · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation On the Opportunities and Risks of Foundation Models
Reference 17
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Observation 96e37ef1-e6f8-444d-8e65-a79199726609 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Cross-domain open-world discovery,
Reference 18
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Observation 4acd1ea3-a408-4fab-ba45-61b83399ce98 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Source-free domain adaptation guided by vision and vision-language pre-training,
Reference 19
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Observation e0320c67-cf04-42f7-8dab-31fc3f6ce917 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Learning transferable visual models from natural language supervision,
Reference 20
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Observation 1533316c-1593-49d0-b943-c8870f2720eb · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Source-free domain adaptation with frozen multimodal foundation model,
Reference 21
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Observation 5f528e43-e836-4ff0-991c-c047bc58a704 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Learning transfer- able features with deep adaptation networks,
Reference 22
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Observation 7dc35160-57b8-4d0f-ae37-c90cbb3b51c1 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Deep transfer learning with joint adaptation networks,
Reference 23
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Unavailable: canonical work link unavailable.
Observation 0229148d-b868-446d-a934-dfe65a3c5684 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Domain-adversarial training of neural networks,
Reference 24
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Observation f7813533-6753-43fa-808d-dfe69b8f17ca · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Domain prompt tuning via meta relabeling for unsupervised adversarial adaptation,
Reference 25
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Observation d7576304-ab9d-4c19-a938-62fd7681c860 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Cross- domain contrastive learning for unsupervised domain adaptation,
Reference 26
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Observation 387fdb99-5243-4724-b3d8-78392d38ce19 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Coarse helps fine: A multi- granularity discriminative adversarial network for fine-grained open- set domain adaptation,
Reference 27
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Observation 3264be7a-9dcc-485b-b2a3-090dae2b673d · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation,
Reference 28
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Observation 1a1f4c4b-e4c3-4d67-a486-a9370ca3a8e0 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Self-mining the confident prototypes for source-free unsupervised domain adaptation in image segmentation,
Reference 29
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Observation 482887dc-c710-4907-ba7b-18f007118c6f · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Domain-division based progressive learning for source-free domain adaptation,
Reference 30
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Observation 64626253-1a18-40ca-b395-f29265e5a530 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Hierarchical unsupervised relation distillation for source-free domain adaptation,
Reference 31
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Observation 7722207e-3a02-4cc1-a3a3-884f4ad4692d · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation De- confusing pseudo-labels in source-free domain adaptation,
Reference 32
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Observation 6d0f9dec-a790-40f3-b27c-5710b4cec7fa · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Robust nearest neighbors for source-free domain adaptation under class distribution shift,
Reference 33
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Observation 69fb1c2a-3cdb-4715-85d4-80ff6d443629 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Multi- granularity class prototype topology distillation for class-incremental source-free unsupervised domain adaptation,
Reference 34
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Observation 70038151-e892-4ba8-95fb-5088ad60ac3b · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Simplifying source-free domain adaptation for object detection: Effective self-training strategies and per- formance insights,
Reference 35
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Observation 658fc958-1959-4f42-a931-dd08f7f4a030 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Source-free unsu- pervised domain adaptation: A survey,
Reference 36
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Observation 811c8eb9-abb7-4fc9-a975-b31da390d1db · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation GPT-4 Technical Report
Reference 37
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Observation 5dc1bf2f-74a7-4e72-bbe8-f79d67fa6759 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Universal Domain Adaptation from Foundation Models: A Baseline Study
Reference 38
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Observation 5b5ce8d8-b3be-46c0-ac85-92474bba2742 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Open-set domain adaptation with visual- language foundation models,
Reference 39
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Observation c0205ca4-587a-476b-9917-d768fe098216 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Decoupling domain invariance and variance with tailored prompts for open-set domain adaptation,
Reference 40
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Observation 02a60fcb-7f83-46a7-bab1-7ab2b10c336f · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Cosmo: Clip talks on open-set multi-target domain adaptation,
Reference 41
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Observation b9772554-823d-4c64-ba97-abcd58065a7c · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Adversarial experts model for black-box domain adaptation,
Reference 42
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Observation 25038ffd-a7c6-42db-89ca-e74952490757 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Envisioning outlier exposure by large language models for out-of-distribution detec- tion,
Reference 43
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Observation 065fcc97-37bc-421a-acc3-9faadede0f46 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Deep residual learning for image recognition,
Reference 44
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Observation fb31e04b-2b9c-48f3-b460-487efd72958c · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Monitoring the coefficient of variation: A literature review,
Reference 45
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Observation 4b2c6e96-4fc0-485b-a86b-80e6cb687aea · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Guiding pseudo-labels with uncertainty estimation for source-free unsupervised domain adaptation,
Reference 46
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Observation f40a9938-e4d6-4337-a32d-32eb91ec48e8 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Adapting visual cate- gory models to new domains,
Reference 47
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Observation 308245d9-ee50-42ec-b276-2d5b30506e86 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Deep hashing network for unsupervised domain adaptation,
Reference 48
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Observation bafa8b0e-75ab-4136-a9a9-4342a48c0a21 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation VisDA: The Visual Domain Adaptation Challenge
Reference 49
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Observation 538b98d7-779b-4f0e-84c1-462d91dd6ef3 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Moment matching for multi-source domain adaptation,
Reference 50
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Observation 2f0439d8-e88c-4034-9911-695dc9805e02 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Attention is all you need,
Reference 51
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Observation bcd55783-d1ff-4bd5-8dce-f307ec0d1352 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Billion-scale similarity search with GPUs,
Reference 52
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Observation 1fd658b4-d724-4162-bb78-8e46a01420a7 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Wdan: A weighted discriminative adversarial network with dual classifiers for fine-grained open-set do- main adaptation,
Reference 53
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Observation 2337503f-63a0-48e9-9dc2-178ccd36c8f0 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Domain consensus clustering for universal domain adaptation,
Reference 54
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Observation 2d7ea3f0-8cca-4a82-99e9-3f409c47219f · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Ovanet: One-vs-all network for universal do- main adaptation,
Reference 55
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Observation 21b9023c-830c-4dbd-a16e-b27e2bbcce7c · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Unified optimal transport framework for universal domain adaptation,
Reference 56
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Observation 0c124433-8a1c-47ba-a321-588c36dbd53d · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Conditional adversarial domain adaptation,
Reference 57
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Observation c6e3c1ee-13e5-446d-ae30-507968966df3 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Bridging theory and algo- rithm for domain adaptation,
Reference 58
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Observation d9ef5840-e00a-44a2-bf7f-ebde8f637766 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Visualizing data using t-sne
Reference 59
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Observation 8fd5a3a9-878a-45d6-a24e-e41a43f6caf3 · outbound
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation Grad-cam: Visual explanations from deep networks via gradient-based localization,
Reference 60
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No inbound Pith citation observations are available.