Paper Citation Record · LEDGER

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization

As of 17 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.17684.

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

pith.paper-citation-record.v1
2505.17684 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:45:28.378330Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

verified exact0
verified fuzzy36
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71348910-474d-475e-bce4-f4be433755e3 · outbound

This paper cites A Comprehensive Framework for 5G Indoor Localization,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization A Comprehensive Framework for 5G Indoor Localization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:35.582514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75747a5d-c4ac-4825-9d45-28b19ab0c0fd · outbound

This paper cites Transfer Learning to Adapt 5G AI-based Fingerprint Localization Across Environments,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Transfer Learning to Adapt 5G AI-based Fingerprint Localization Across Environments,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:35.345839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e35095b8-fbad-47a7-855d-b14a580e0db5 · outbound

This paper cites Wiometrics: Comparative Performance of Artificial Neural Networks for Wireless Navigation,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Wiometrics: Comparative Performance of Artificial Neural Networks for Wireless Navigation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:35.160723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation de4d1db2-8aa3-427f-8279-8549dad59423 · outbound

This paper cites 5G Positioning Advancements with AI/ML.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization 5G Positioning Advancements with AI/ML

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:25.419094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca9ac08e-c93a-41bc-9181-8af77e493a98 · outbound

This paper cites Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.936527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5e6e52a4-65ba-4b84-bac9-bd5d6d47ec39 · outbound

This paper cites FeMLoc: Federated Meta- learning for Adaptive Wireless Indoor Localization Tasks in IoT Net- works,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization FeMLoc: Federated Meta- learning for Adaptive Wireless Indoor Localization Tasks in IoT Net- works,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.742205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d6f68b2-75f1-40b4-9ea0-ea4f4850a5af · outbound

This paper cites Mitigating Catastrophic Forgetting in Deep Transfer Learning for Fingerprinting Indoor Posi- tioning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Mitigating Catastrophic Forgetting in Deep Transfer Learning for Fingerprinting Indoor Posi- tioning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.557823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8b7a6d90-af45-4aeb-b3b3-29304d5f051b · outbound

This paper cites Uncovering the Potential of Indoor Localization: Role of Deep and Transfer Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Uncovering the Potential of Indoor Localization: Role of Deep and Transfer Learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.378343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 935e9086-5e59-4fe1-98a2-b832dbd4a18a · outbound

This paper cites Indoor Localization in Commercial 5G Environment with Single BS,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Indoor Localization in Commercial 5G Environment with Single BS,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.197622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23d058c5-7364-464b-a20e-e602da65f438 · outbound

This paper cites Deep Learning-based Positioning with Multi-task Learning and Uncertainty-based Fusion,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Deep Learning-based Positioning with Multi-task Learning and Uncertainty-based Fusion,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:34.046635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0b347804-6af9-4e27-8a2f-54ad557ea9ee · outbound

This paper cites A Tutorial on Terahertz-Band Localization for 6G Communication Systems,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization A Tutorial on Terahertz-Band Localization for 6G Communication Systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:33.867626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 846b9f53-c7fb-40c8-8bde-64f1d182c636 · outbound

This paper cites A CSI- Based Data-Driven Localization Framework Using Small-Scale Training Datasets in Single-Site MIMO Systems,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization A CSI- Based Data-Driven Localization Framework Using Small-Scale Training Datasets in Single-Site MIMO Systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:33.640031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3a8bc8c0-29c4-4b26-84c7-31054fda9f26 · outbound

This paper cites Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:26.159914Z

Source-reported events for the cited work

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Observation da9ea18a-b460-4b7f-8698-92a58b8ed4fe · outbound

This paper cites 5G1M: Indoor Fingerprint Positioning Using a Single 5G Module,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization 5G1M: Indoor Fingerprint Positioning Using a Single 5G Module,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:33.515224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ead94bc1-f54d-4eb8-b7a9-2a7bcb7b8796 · outbound

This paper cites RSSI-based Fingerprint Localization in LoRaW AN Networks Using CNNs with Squeeze and Excitation Blocks,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization RSSI-based Fingerprint Localization in LoRaW AN Networks Using CNNs with Squeeze and Excitation Blocks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:33.346199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b9a53760-09bc-46b2-9ee5-5a2c914e07d8 · outbound

This paper cites SNWPM: A Siamese Network Based Wireless Positioning Model Resilient to Partial Base Stations Unavailable,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization SNWPM: A Siamese Network Based Wireless Positioning Model Resilient to Partial Base Stations Unavailable,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:33.065058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ef0e19fd-82e6-47bf-910f-fc56cb4313b7 · outbound

This paper cites Im- plementation of a Transfer Learning and Fingerprint-Based Positioning System,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Im- plementation of a Transfer Learning and Fingerprint-Based Positioning System,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:32.789920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d33bb613-099e-4b34-b69e-d083faad74a0 · outbound

This paper cites An Attention Auxiliary Network- Based Method for WiFi Fingerprint Indoor Localization,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization An Attention Auxiliary Network- Based Method for WiFi Fingerprint Indoor Localization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:32.528348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 734b165d-1b04-4e60-babe-a6dec19b0a09 · outbound

This paper cites Progressive Neural Networks.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Progressive Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:26.586639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 510fad91-193e-4143-9d9a-a48746c1e431 · outbound

This paper cites Continual Learning Through Synaptic Intelligence,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Continual Learning Through Synaptic Intelligence,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:32.208080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7f952189-3997-4940-8f23-3935ad06b3b9 · outbound

This paper cites Experi- ence Replay for Continual Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Experi- ence Replay for Continual Learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:32.055593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8b90604b-5ae5-42ed-ad95-0b758f2ec18d · outbound

This paper cites Overcoming Catastrophic Forgetting in Neural Networks,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Overcoming Catastrophic Forgetting in Neural Networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:31.835642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 414e1af6-5990-4739-be6c-a84014feee07 · outbound

This paper cites Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:26.913598Z

Source-reported events for the cited work

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Observation 8eeab774-05cf-42c3-9aec-c5a5f195c2f9 · outbound

This paper cites Learning Without Forgetting,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Learning Without Forgetting,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:31.563174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bcc6bec9-dba8-4472-8127-4b2f39eda1e6 · outbound

This paper cites DTL-5G: Deep Transfer Learning-based DDoS Attack Detection in 5G and Beyond Networks,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization DTL-5G: Deep Transfer Learning-based DDoS Attack Detection in 5G and Beyond Networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:31.343418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 55ea61c2-499f-4ac5-849e-bb5531a880ff · outbound

This paper cites Dynamic Anomaly Detection in 5G-Connected IoT Devices using Transfer Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Dynamic Anomaly Detection in 5G-Connected IoT Devices using Transfer Learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:31.157096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation db8c4810-82ae-464a-9002-d910c4570fb7 · outbound

This paper cites Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:31.030606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 048bbcd4-c25c-4b78-a7c1-ec82fdc08938 · outbound

This paper cites One-Shot Domain Incremental Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization One-Shot Domain Incremental Learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.864176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e6f2d5d9-b729-42f1-bc32-567460374efd · outbound

This paper cites An Efficient Domain-Incremental Learning Approach to Drive in All Weather Condi- tions,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization An Efficient Domain-Incremental Learning Approach to Drive in All Weather Condi- tions,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.731713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89a38f7a-bc69-4836-9846-102ac0e5309c · outbound

This paper cites Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.532373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fc78aa3c-b5ce-44c5-9c48-805dbc46d125 · outbound

This paper cites Graph-Based vs. Error State Kalman Filter-Based Fusion of 5G and Inertial Data for MA V Indoor Pose Estimation,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Graph-Based vs. Error State Kalman Filter-Based Fusion of 5G and Inertial Data for MA V Indoor Pose Estimation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.400255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b10189e-6f70-404d-9847-550024d03d99 · outbound

This paper cites Neural 5G Indoor Localization with IMU Supervision,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Neural 5G Indoor Localization with IMU Supervision,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.222304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 37f75a8d-7d64-4960-bfa9-52a12a473501 · outbound

This paper cites Non- Exemplar Domain Incremental Learning via Cross-Domain Concept Integration,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Non- Exemplar Domain Incremental Learning via Cross-Domain Concept Integration,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:30.046533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 872b2045-7173-4495-a92f-d5918015ed89 · outbound

This paper cites A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.858014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 07d7c756-6c1f-4ba0-b302-c87cdc4d3259 · outbound

This paper cites Temporal Source Recovery for Time-Series Source-Free Unsupervised Domain Adaptation,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Temporal Source Recovery for Time-Series Source-Free Unsupervised Domain Adaptation,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:27.899395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f86be39c-3ffe-49a9-977d-b0727e150f4f · outbound

This paper cites Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.673648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2352c020-9098-4bb1-b09a-f5c1cd6de5b6 · outbound

This paper cites Indoor Positioning in 5G-Advanced: Challenges and Solution Toward Centimeter-Level Accuracy with Carrier Phase Enhancements,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Indoor Positioning in 5G-Advanced: Challenges and Solution Toward Centimeter-Level Accuracy with Carrier Phase Enhancements,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.524856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9825f06-1015-4ce4-9bd9-11535f993d1d · outbound

This paper cites Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.363545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a3c8fcc8-aaba-4292-bd27-196949e21f84 · outbound

This paper cites Prediction Error- based Classification for Class-Incremental Learning,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Prediction Error- based Classification for Class-Incremental Learning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.208675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94dfd548-1b17-4d6b-8860-7b2c0922f550 · outbound

This paper cites [Online].

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization [Online]

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:29.037698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 29a7ff74-3dfd-4e53-84a9-eff731d3a3ff · outbound

This paper cites Indoor Positioning Technologies,.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Indoor Positioning Technologies,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:45:28.843845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.