Paper Citation Record · LEDGER

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning

As of 22 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2607.20666.

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

pith.paper-citation-record.v1
2607.20666 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T09:44:25.719416Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

21 of 21 outbound references displayed

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verified fuzzy0
unresolved21
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 217ae009-7b87-430e-b986-f6907fad4a17 · outbound

This paper cites On the generalization of cognitive optical networking applications using composable machine learning,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning On the generalization of cognitive optical networking applications using composable machine learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:22.978800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbe458e9-edbc-4cf4-8c1f-8cb9af4d224c · outbound

This paper cites Generalizability of ML-based classification of state of polarization signatures across different bands and links,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Generalizability of ML-based classification of state of polarization signatures across different bands and links,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.073873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8da7e770-63a8-435c-b41c-c65f083efadb · outbound

This paper cites A module to enhance the generalization ability of end- to-end deep learning systems in optical fiber communications,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning A module to enhance the generalization ability of end- to-end deep learning systems in optical fiber communications,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.223166Z

Source-reported events for the cited work

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Observation 97a7f5c3-b0ff-4c5b-b9cb-3660d615832d · outbound

This paper cites Transfer learning aided QoT computation in network operating with the 400ZR standard,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Transfer learning aided QoT computation in network operating with the 400ZR standard,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.356814Z

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Unavailable: canonical work link unavailable.

Observation 7aab0968-66d2-48d3-9546-d64ca5bda935 · outbound

This paper cites Integrating knowledge distillation and transfer learning for en- hanced QoT-estimation in optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Integrating knowledge distillation and transfer learning for en- hanced QoT-estimation in optical networks,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.506478Z

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Unavailable: canonical work link unavailable.

Observation 9a10d8ac-52b3-4a11-8210-a37beab76d55 · outbound

This paper cites Neuron-level transfer learning for ANN-based QoT estimation in optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Neuron-level transfer learning for ANN-based QoT estimation in optical networks,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.631109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d16a30-ab4e-4376-a500-4cc2877ee81c · outbound

This paper cites Evolutionary neuron-level transfer learning for QoT estimation in optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Evolutionary neuron-level transfer learning for QoT estimation in optical networks,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.762795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02bfb5ca-a88b-415f-b490-833e15396127 · outbound

This paper cites QoT estimation with margin-driven transfer learn- ing in time-varying optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning QoT estimation with margin-driven transfer learn- ing in time-varying optical networks,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:23.945794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 558a8cf5-37d3-4afa-a6cc-ccc228a3bfeb · outbound

This paper cites Automated, interpretable and efficient ML models for real-world lightpaths’ quality of transmission estimation,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Automated, interpretable and efficient ML models for real-world lightpaths’ quality of transmission estimation,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.083063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c45fc584-1c0d-44c0-a015-ccd0e55980d4 · outbound

This paper cites Multi-span optical power spectrum prediction using ML-based EDFA models and cascaded learning,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Multi-span optical power spectrum prediction using ML-based EDFA models and cascaded learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.211076Z

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Observation a60e5bb3-6308-47d4-b011-ae004309ec57 · outbound

This paper cites Leveraging shared data and models for ML-based QoT estimation: Toward standardized and generalizable models,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Leveraging shared data and models for ML-based QoT estimation: Toward standardized and generalizable models,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.289271Z

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Observation 26bb8edc-0327-42e1-8972-d4077cfd123b · outbound

This paper cites One-shot learning for modulation format identifica- tion in evolving optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning One-shot learning for modulation format identifica- tion in evolving optical networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.451802Z

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Observation 7a0b3bfc-e8a0-4bc8-9f86-37c9d7626ee8 · outbound

This paper cites Fault tracing based on Siamese neural network for optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Fault tracing based on Siamese neural network for optical networks,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.647559Z

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Observation 954a154c-9f17-44a4-a37a-f164b8242f25 · outbound

This paper cites A unified Siamese learning framework for zero-day anomaly detection and classification in optical networks,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning A unified Siamese learning framework for zero-day anomaly detection and classification in optical networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.805589Z

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Unavailable: canonical work link unavailable.

Observation aa814e72-ed4d-4047-8d2b-3d615e2d0ad7 · outbound

This paper cites Deep metric learning using triplet network,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Deep metric learning using triplet network,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:24.998207Z

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Observation 381389a3-06fc-43e0-b865-95eec165a993 · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Facenet: A unified embedding for face recognition and clustering,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.108673Z

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Observation 84fe9184-5ff6-40e3-870d-784e49c7522d · outbound

This paper cites Multi-similarity loss with general pair weighting for deep metric learning,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Multi-similarity loss with general pair weighting for deep metric learning,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.197226Z

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Observation c6a4993f-7899-469d-b1ce-f7526e82388d · outbound

This paper cites Dimensionality reduction by learning an invariant mapping,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning Dimensionality reduction by learning an invariant mapping,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.358991Z

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Unavailable: canonical work link unavailable.

Observation eeaa0c01-e731-4ee0-b236-e8e86f74a733 · outbound

This paper cites PyTorch Metric Learning.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning PyTorch Metric Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.492857Z

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Observation dcf4b434-6032-49d2-b77d-9727865919df · outbound

This paper cites ML-assisted QoT estimation: a dataset collection and data visualization for dataset quality evaluation,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning ML-assisted QoT estimation: a dataset collection and data visualization for dataset quality evaluation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.621215Z

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Observation 55ac102a-f49c-4e7d-b4a0-8523d107246a · outbound

This paper cites QoT dataset collection,.

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning QoT dataset collection,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T09:44:25.719416Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.