Paper Citation Record · LEDGER

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2504.14994.

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

pith.paper-citation-record.v1
2504.14994 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:39:44.790496Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

41 of 41 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a58e881-47cc-4234-980a-3a5743c6c82e · outbound

This paper cites Time series domain adaptation via sparse associative structure alignment.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Time series domain adaptation via sparse associative structure alignment

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.404879Z

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Observation 88e8d73c-03f6-429c-af6d-542f906e3258 · outbound

This paper cites Homm: Higher-order moment matching for unsupervised domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Homm: Higher-order moment matching for unsupervised domain adaptation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.389718Z

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Observation 7369ee9f-bd80-461e-b1c3-c5214c3e4a1b · outbound

This paper cites Domain-adversarial training of neural networks.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Domain-adversarial training of neural networks

Reference 3

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Source-reported events for the cited work

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Observation f5daeca5-4689-4e98-b223-1b2e52af043e · outbound

This paper cites Deep reconstruction-classification networks for unsupervised domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Deep reconstruction-classification networks for unsupervised domain adaptation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.363635Z

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Observation 8f34cff9-32f0-4668-8c66-fff2b24e5954 · outbound

This paper cites Sotta: Robust test-time adaptation on noisy data streams.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Sotta: Robust test-time adaptation on noisy data streams

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.349503Z

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Observation d5ac9371-f16a-41d2-9ce1-bbf971ebc845 · outbound

This paper cites Sparse binary transformers for multivariate time series modeling.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Sparse binary transformers for multivariate time series modeling

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.335091Z

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Observation 7c8e2e4c-444a-462e-a2f8-b360f3a3aac7 · outbound

This paper cites Domain adaptation for time series under feature and label shifts.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Domain adaptation for time series under feature and label shifts

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.320821Z

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Observation 225b195d-4e99-401a-88df-968615443a20 · outbound

This paper cites Swl-adapt: An unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Swl-adapt: An unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.304972Z

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Observation 51d3dfd9-1cde-4bf7-8165-c1c99a6b489e · outbound

This paper cites Sf-adapter: Computational-efficient source-free domain adaptation for human activity recognition.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Sf-adapter: Computational-efficient source-free domain adaptation for human activity recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.289523Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ec135198-103d-4c9a-ba07-16a3159fc44e · outbound

This paper cites Time series as images: Vision transformer for irregularly sampled time series.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Time series as images: Vision transformer for irregularly sampled time series

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.274990Z

Source-reported events for the cited work

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Observation 42ac1b9e-3f65-4257-9e24-0d1058144a3e · outbound

This paper cites Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.260539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af38001f-8285-41af-9016-ce218bdae3ba · outbound

This paper cites TTN: A Domain-Shift Aware Batch Normalization in Test-Time Adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation TTN: A Domain-Shift Aware Batch Normalization in Test-Time Adaptation

Reference 12

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Source-reported events for the cited work

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Observation 804aa62d-c908-4ea4-8558-819e0866c211 · outbound

This paper cites Timesurl: Self-supervised contrastive learning for universal time series representation learning.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Timesurl: Self-supervised contrastive learning for universal time series representation learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.245464Z

Source-reported events for the cited work

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Observation 068ad8e0-ebe8-4fb6-a64c-9c89b44b237e · outbound

This paper cites Adversarial spectral kernel matching for unsupervised time series domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Adversarial spectral kernel matching for unsupervised time series domain adaptation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.231116Z

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Observation 20f14f73-f8fb-4e56-be08-37cd7292496a · outbound

This paper cites Conditional adversarial domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Conditional adversarial domain adaptation

Reference 15

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Observation ce5d498e-8d00-47db-b098-73f47d20b6e8 · outbound

This paper cites Fft-trans: Enhancing robustness in mechanical fault diagnosis with fourier transform-based transformer under noisy conditions.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Fft-trans: Enhancing robustness in mechanical fault diagnosis with fourier transform-based transformer under noisy conditions

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.207254Z

Source-reported events for the cited work

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Observation f770c1b3-3b4d-4cf6-8ddb-4bdc31b6f525 · outbound

This paper cites Mhccl: masked hierarchical cluster-wise contrastive learning for multivariate time series.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Mhccl: masked hierarchical cluster-wise contrastive learning for multivariate time series

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.190759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a352fe82-5413-41c4-8918-e011a3693583 · outbound

This paper cites Formertime: hierarchical multi-scale representations for multivariate time series classification.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Formertime: hierarchical multi-scale representations for multivariate time series classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.176756Z

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Observation 1185187e-0ed6-4fa8-8e6f-8e088ed75b83 · outbound

This paper cites Towards Stable Test-Time Adaptation in Dynamic Wild World.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Towards Stable Test-Time Adaptation in Dynamic Wild World

Reference 19

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Observation 842a0ef9-aa0a-449d-b90c-c25e35b7b716 · outbound

This paper cites Towards interpretable sleep stage classification using cross-modal transformers.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Towards interpretable sleep stage classification using cross-modal transformers

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.162258Z

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Observation cc41de6a-875b-4f63-9b81-0aae8aa1b36a · outbound

This paper cites Adaptive intermediate class-wise distribution alignment: a universal domain adaptation and generalization method for machine fault diagnosis.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Adaptive intermediate class-wise distribution alignment: a universal domain adaptation and generalization method for machine fault diagnosis

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.146870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cedf6f44-888d-4b3c-a9be-b7a63fc79c1a · outbound

This paper cites Adatime: A benchmarking suite for domain adaptation on time series data.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Adatime: A benchmarking suite for domain adaptation on time series data

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.129997Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bb449773-6086-4c16-aaec-388254929581 · outbound

This paper cites Source-free domain adaptation with temporal imputation for time series data.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Source-free domain adaptation with temporal imputation for time series data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.114730Z

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Observation ce93c1f3-0ef8-4348-90ed-da96534ee9e1 · outbound

This paper cites On minimum discrepancy estimation for deep domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation On minimum discrepancy estimation for deep domain adaptation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.099831Z

Source-reported events for the cited work

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Observation 4b7ddd47-60e1-4991-a65c-0e21bc8bdde4 · outbound

This paper cites Correlation alignment for unsupervised domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Correlation alignment for unsupervised domain adaptation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.085146Z

Source-reported events for the cited work

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Observation 9b38ab58-74e4-4721-9dbe-4b7a92eb43d8 · outbound

This paper cites A universal multi-source domain adaptation method with unsupervised clustering for mechanical fault diagnosis under incomplete data.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation A universal multi-source domain adaptation method with unsupervised clustering for mechanical fault diagnosis under incomplete data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.070365Z

Source-reported events for the cited work

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Observation f5e253f6-5ab5-4a94-a242-c9e9ba230637 · outbound

This paper cites Deep Domain Confusion: Maximizing for Domain Invariance.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Deep Domain Confusion: Maximizing for Domain Invariance

Reference 27

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Observation 11963ca8-4a41-4184-b278-726a2ac0a796 · outbound

This paper cites Neural discrete representation learning.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Neural discrete representation learning

Reference 28

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Source-reported events for the cited work

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Observation 845b44db-8467-4f29-a190-41468076d349 · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 29

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Source-reported events for the cited work

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Observation 4ca5c305-ac25-4ada-a1a7-90a1be1dabd8 · outbound

This paper cites When: A wavelet-dtw hybrid attention network for heterogeneous time series analysis.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation When: A wavelet-dtw hybrid attention network for heterogeneous time series analysis

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.047423Z

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Observation 03c1abf1-494a-4e0c-b28f-b65b5c2afea0 · outbound

This paper cites Pond: Multi-source time series domain adaptation with information-aware prompt tuning.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Pond: Multi-source time series domain adaptation with information-aware prompt tuning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.033046Z

Source-reported events for the cited work

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Observation 9cc51891-c584-4db6-adde-d16558d576d6 · outbound

This paper cites Multi-source deep domain adaptation with weak supervision for time-series sensor data.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Multi-source deep domain adaptation with weak supervision for time-series sensor data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.018028Z

Source-reported events for the cited work

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Observation a684aa80-cf90-405c-8c8c-c09b6283d7ca · outbound

This paper cites Calda: Improving multi-source time series domain adaptation with contrastive adversarial learning.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Calda: Improving multi-source time series domain adaptation with contrastive adversarial learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:45.003915Z

Source-reported events for the cited work

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Observation 5e8536f0-0fb2-48dc-8d7c-7606ebcab097 · outbound

This paper cites Privacy-preserving domain adaptation for motor imagery-based brain-computer interfaces.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Privacy-preserving domain adaptation for motor imagery-based brain-computer interfaces

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.989929Z

Source-reported events for the cited work

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Observation be630be4-71ee-4c20-aeea-a7011ad80886 · outbound

This paper cites Channel attention for sensor-based activity recognition: embedding features into all frequencies in dct domain.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Channel attention for sensor-based activity recognition: embedding features into all frequencies in dct domain

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.974730Z

Source-reported events for the cited work

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Observation baa0c5c1-64a6-49b1-b386-74b6c7d2d48d · outbound

This paper cites Exploiting the intrinsic neighborhood structure for source-free domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Exploiting the intrinsic neighborhood structure for source-free domain adaptation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.959166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5f3cab33-244f-43d7-8e38-5747854688b5 · outbound

This paper cites Attracting and dispersing: A simple approach for source-free domain adaptation.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Attracting and dispersing: A simple approach for source-free domain adaptation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.943899Z

Source-reported events for the cited work

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Observation caf4c90f-da79-4f64-8cfa-b8f915b676f2 · outbound

This paper cites Deep generative domain adaptation with temporal relation attention mechanism for cross-user activity recognition.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Deep generative domain adaptation with temporal relation attention mechanism for cross-user activity recognition

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.929177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ae7aa16b-78ab-4b59-bbe8-86bc0e8dc16a · outbound

This paper cites Self-supervised contrastive pre-training for time series via time-frequency consistency.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Self-supervised contrastive pre-training for time series via time-frequency consistency

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.913366Z

Source-reported events for the cited work

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Observation e01c3dfc-4393-4ee5-b1eb-1b805c4af0ce · outbound

This paper cites Multi-modal sleep stage classification with two-stream encoder-decoder.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Multi-modal sleep stage classification with two-stream encoder-decoder

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.897513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c0add448-93fb-49df-af8a-57fccd3b0188 · outbound

This paper cites Deep representation-based domain adaptation for nonstationary eeg classification.

Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation Deep representation-based domain adaptation for nonstationary eeg classification

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:39:44.881259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.