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Paper Citation Record · LEDGER

Domain Adaptation: Learning Bounds and Algorithms

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:0902.3430.

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

pith.paper-citation-record.v1
0902.3430 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:07:19.822306Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T23:45:06.096833Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cbfe9c08-2933-472f-b2de-2dab5da33be6 · inbound

Quantifying Error in the Presence of Confounders for Causal Inference cites this paper.

Quantifying Error in the Presence of Confounders for Causal Inference Domain Adaptation: Learning Bounds and Algorithms

Reference 11

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verified exact
arxiv_id, observed 2026-05-24T23:45:06.100073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T23:43:26.320712Z digest=sha256:ab7eac2589a83631976eb30d6f63bc613da97fdc2d730aa161c1ce6e0075648b

Observation 6af6a658-1e63-4fe2-ba24-732d35bd06ca · inbound

Lightspeed Geometric Dataset Distance via Sliced Optimal Transport cites this paper.

Lightspeed Geometric Dataset Distance via Sliced Optimal Transport Domain Adaptation: Learning Bounds and Algorithms

Reference 32

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no resolver link, observed 2026-08-09T22:07:19.822306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:07:19.822306Z digest=sha256:1b56bc8821cdaedc0e6d29445e8428147f772dbd79c90e68752f223e4226482a

Observation cbff4516-464b-4687-b40f-b15601b44d84 · inbound

Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation cites this paper.

Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation Domain Adaptation: Learning Bounds and Algorithms

Reference 39

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no resolver link, observed 2026-08-08T20:58:04.045264Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:58:04.045264Z digest=sha256:025cf79faf553140109a33da87ff0ec331f3f0341ecf53000f7beea053ff2779

Observation 31780883-f6ca-4c98-ae2e-04a56342927f · inbound

Computational Efficiency under Covariate Shift in Kernel Ridge Regression cites this paper.

Computational Efficiency under Covariate Shift in Kernel Ridge Regression Domain Adaptation: Learning Bounds and Algorithms

Reference 2011

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no resolver link, observed 2026-08-07T15:42:27.225168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:27.225168Z digest=sha256:d727fc9d702c028b3d70c0b97ae76584a83ed6761470234a5d56be95c1683c29

Observation d5ee8f53-8ef7-493a-a06e-f6b87a8640a0 · inbound

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective cites this paper.

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective Domain Adaptation: Learning Bounds and Algorithms

Reference 32

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no resolver link, observed 2026-08-07T13:55:27.160532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:55:27.160532Z digest=sha256:9f52a2ff8cf4499c48800e9f9b79327798021a3351621f8e77a7edbf08a16b70

Observation b25bc6d7-d8dc-4a2d-97a9-54cd21cd1f2d · inbound

Subgroups Matter for Robust Bias Mitigation cites this paper.

Subgroups Matter for Robust Bias Mitigation Domain Adaptation: Learning Bounds and Algorithms

Reference 38

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no resolver link, observed 2026-08-07T13:42:12.443220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:42:12.443220Z digest=sha256:1527461f5fb5e2da869b2048e2b392066ea07dce73b2a45181485104e764a13b

Observation 2b1e2d32-60ce-467f-aef2-4ede4053c6cd · inbound

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation cites this paper.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain Adaptation: Learning Bounds and Algorithms

Reference 42

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no resolver link, observed 2026-08-07T13:23:17.886810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:23:17.886810Z digest=sha256:44d71a9ae7f95ae185b6444df12c851dc0aeced542e4e21b414f7f574d38e2c4

Observation 9481205b-e373-49c5-82f5-0a4e7dcd13b4 · inbound

Best Arm Identification with Possibly Biased Offline Data cites this paper.

Best Arm Identification with Possibly Biased Offline Data Domain Adaptation: Learning Bounds and Algorithms

Reference 2025

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no resolver link, observed 2026-08-07T13:07:12.935573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:07:12.935573Z digest=sha256:4f98a442e48f2d6c74e837bb337dec7414e002b13ac147848cb032aa483af430

Observation 2df69bac-029e-42b8-a26c-3ad6bd9e8518 · inbound

Clustered Federated Learning via Embedding Distributions cites this paper.

Clustered Federated Learning via Embedding Distributions Domain Adaptation: Learning Bounds and Algorithms

Reference 2023

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no resolver link, observed 2026-08-07T05:32:23.040252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:32:23.040252Z digest=sha256:7f1569ef14ac6bcc04ca9a15446b229ce47060529328f3d82f4da4483e21c6c4

Observation 28549a2c-7a88-4722-82f4-9cadd45fa681 · inbound

Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition cites this paper.

Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition Domain Adaptation: Learning Bounds and Algorithms

Reference 71

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no resolver link, observed 2026-08-06T22:40:16.219111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:40:16.219111Z digest=sha256:0cd1722b4701ad809a3fedb7a94d15936d6d74e2d93cacaffb8aabb076eb9ce3

Observation 569ce701-0b4e-48db-acc8-540baf285871 · inbound

Phase Transition in Nonparametric Minimax Rates for Covariate Shifts on Approximate Manifolds cites this paper.

Phase Transition in Nonparametric Minimax Rates for Covariate Shifts on Approximate Manifolds Domain Adaptation: Learning Bounds and Algorithms

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:19:14.080173Z digest=sha256:bdd2f8a450363b766ae9319f7f8039044d7f7c16627e5cda0347cfe5fc49c0af

Observation 44f7e6a2-fae2-4885-9516-c65a429bf70e · inbound

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning cites this paper.

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning Domain Adaptation: Learning Bounds and Algorithms

Reference 8

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no resolver link, observed 2026-08-06T20:02:30.745648Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:02:30.745648Z digest=sha256:386dbb6c2132d02192df3e9ab0590b1307bc7bc0746d4af203766c6b150ae280

Observation e8adc932-6f43-457c-8189-c16732318cad · inbound

Enhancing Fatigue Detection through Heterogeneous Multi-Source Data Integration and Cross-Domain Modality Imputation cites this paper.

Enhancing Fatigue Detection through Heterogeneous Multi-Source Data Integration and Cross-Domain Modality Imputation Domain Adaptation: Learning Bounds and Algorithms

Reference 64

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no resolver link, observed 2026-08-06T15:27:22.587873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:22.587873Z digest=sha256:bf4085720b79d7bcf2aa72795ac606ce0a7097e4f810cf5429b22607e4c4c8cf

Observation 958cd435-629c-445e-807e-0b77ef17da02 · inbound

ACE and Diverse Generalization via Selective Disagreement cites this paper.

ACE and Diverse Generalization via Selective Disagreement Domain Adaptation: Learning Bounds and Algorithms

Reference 56

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no resolver link, observed 2026-08-04T21:33:24.040136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:33:24.040136Z digest=sha256:8ada05453a38a8a6c6443e12e28805e73919efd94b9ba1853c990c4b219b8ca0

Observation 9a042263-49c4-4283-8830-8179dd6f09b9 · inbound

Transformers for dynamical systems learn transfer operators in-context cites this paper.

Transformers for dynamical systems learn transfer operators in-context Domain Adaptation: Learning Bounds and Algorithms

Reference 21

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verified exact
arxiv_id, observed 2026-05-15T20:20:17.461053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T20:19:10.613541Z digest=sha256:722a0a8bf88126e4524ee93365f0111523d5a78b3cc4fbe1204b025365c409f6

Observation b3bab9e1-470a-4492-836e-ca402ed8bcd0 · inbound

From Weights to Activations: Is Steering the Next Frontier of Adaptation? cites this paper.

From Weights to Activations: Is Steering the Next Frontier of Adaptation? Domain Adaptation: Learning Bounds and Algorithms

Reference 13

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metadata mismatch
arxiv_id, observed 2026-05-10T12:55:24.630408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T12:52:58.193141Z digest=sha256:2c0fd0533e73e794951c690431404922466cfd5847c16808b721ada0f2eb7b94

Observation 4d69bd2d-f04b-4996-aaea-881c8b4ca873 · inbound

Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models cites this paper.

Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models Domain Adaptation: Learning Bounds and Algorithms

Reference 97

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arxiv_id, observed 2026-05-11T15:16:11.107354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-09T20:20:20.864444Z digest=sha256:63d966a3c95acd5e1f122be07f578776dc3d27e564befaa9ea7500c9a380e54c

Observation 7553708b-914b-41ab-9149-8c5cd7be24d8 · inbound

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift cites this paper.

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift Domain Adaptation: Learning Bounds and Algorithms

Reference 73

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arxiv_id, observed 2026-05-12T07:21:25.323129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T03:27:41.845716Z digest=sha256:f5843025ae3d1a60cbec0a9fa0825932ef865f01b98739c36ad6d4c9828d6630

Observation 113ca521-dcf3-4100-8af5-37f0d3b2a36e · inbound

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift cites this paper.

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift Domain Adaptation: Learning Bounds and Algorithms

Reference 73

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arxiv_id, observed 2026-05-20T22:09:07.596724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T22:04:57.245024Z digest=sha256:63fb1fde89b4c04ccf7e60600fd60edb992efd5da9912de0668a9fcc6706963d

Observation 08d34ace-8d5f-4eab-a170-50ab8cdad6a2 · inbound

Adaptive Kernel Ridge Regression with Linear Structure: Sharp Oracle Inequalities and Minimax Optimality cites this paper.

Adaptive Kernel Ridge Regression with Linear Structure: Sharp Oracle Inequalities and Minimax Optimality Domain Adaptation: Learning Bounds and Algorithms

Reference 139

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arxiv_id, observed 2026-05-13T04:57:17.811846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T04:45:28.262509Z digest=sha256:083a9b9b5394a052462a53224ad040640693832a9f5396f8bbd0126ebd3bb771

Observation 7c8644b0-ecdd-4a19-a25c-afe7822e0a09 · inbound

Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles cites this paper.

Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles Domain Adaptation: Learning Bounds and Algorithms

Reference 16

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arxiv_id, observed 2026-05-14T20:32:56.546502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T20:32:12.744422Z digest=sha256:001330a330e0ed2cf10dc607a770d13ecb993bbd7aa2886845ccabdd7d9e7618

Observation c99a2ecb-1c2b-42dc-9dcf-b629ae709e9e · inbound

YOLOv14: Adaptive Real-Time Object Detection for Diverse Imaging Conditions cites this paper.

YOLOv14: Adaptive Real-Time Object Detection for Diverse Imaging Conditions Domain Adaptation: Learning Bounds and Algorithms

Reference 32

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no resolver link, observed 2026-08-06T18:10:14.750205Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:10:14.750205Z digest=sha256:13c665a83961fd8aa95bd9955d3bf76c883b56bc56ec6f0ba9b1a31d113a278a

Observation ec45fb42-8b33-4a96-9cd5-53a3755cb8d2 · inbound

Nonparametric Goodness-of-fit Testing under Covariate Shift cites this paper.

Nonparametric Goodness-of-fit Testing under Covariate Shift Domain Adaptation: Learning Bounds and Algorithms

Reference 24

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no resolver link, observed 2026-08-06T14:53:47.163424Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:53:47.163424Z digest=sha256:8bc6515dbb51b20e12fc0bdc69b8604f65c68492dc56bb1f66d6fe4dee837291

Observation 27e0666c-9ee9-4d84-a3c9-ea6612f3577f · inbound

Nonparametric Goodness-of-fit Testing under Covariate Shift cites this paper.

Nonparametric Goodness-of-fit Testing under Covariate Shift Domain Adaptation: Learning Bounds and Algorithms

Reference 24

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no resolver link, observed 2026-08-08T17:40:03.491642Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:40:03.491642Z digest=sha256:6c1044b127ee4468299b047c72e3ac564487f894ff7fd0264761e37f94cd28e7