Paper Citation Record · LEDGER

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks?

As of 12 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2509.03077.

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

pith.paper-citation-record.v1
2509.03077 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:10:43.530507Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:24:47.576337Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:24:49.792575Z

Reference resolution

13 of 13 outbound references displayed

verified exact3
verified fuzzy10
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 11a900b1-4904-4c5a-88c5-6dca6bdef674 · outbound

This paper cites Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:10:43.662899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9e83c35-440b-4b12-abea-33de8fc31bb9 · outbound

This paper cites SAM-CLIP: Merging vision foundation models towards semantic and spatial under- standing,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? SAM-CLIP: Merging vision foundation models towards semantic and spatial under- standing,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.901374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8afa7912-9aee-478a-bf2d-13939e34a43f · outbound

This paper cites Self-Supervised Multimodal Learning: A Survey.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Self-Supervised Multimodal Learning: A Survey

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:10:43.627020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4604c340-01b1-4d35-aa12-232e98a650f6 · outbound

This paper cites Self-supervised radio-visual representation learning for 6G sensing,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Self-supervised radio-visual representation learning for 6G sensing,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.877991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb31b4d3-1920-45f9-a880-07967e586ce1 · outbound

This paper cites Self-supervised learning for enhancing angular resolution in automotive MIMO radars,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Self-supervised learning for enhancing angular resolution in automotive MIMO radars,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.857691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c29ff85e-3d58-4a86-b675-da5e8878d32d · outbound

This paper cites Self-supervised RF signal representation learning for NextG signal clas- sification with deep learning,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Self-supervised RF signal representation learning for NextG signal clas- sification with deep learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.829706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 91cb2701-8e9f-443b-98d7-409b74d906c1 · outbound

This paper cites Unsupervised learning for human sensing using radio signals,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Unsupervised learning for human sensing using radio signals,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.807839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6c03f055-919e-45ad-8c01-3202462f665f · outbound

This paper cites Bootstrapping autonomous driving radars with self-supervised learn- ing,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Bootstrapping autonomous driving radars with self-supervised learn- ing,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.784986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6624f810-ee7d-4f91-bc9e-7039b68c90c1 · outbound

This paper cites A self-supervised learning-based channel estimation for IRS-aided communication without ground truth,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? A self-supervised learning-based channel estimation for IRS-aided communication without ground truth,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.762516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation debdbf51-697d-411d-ad96-79cb6382804a · outbound

This paper cites A specific emitter identification method based on self-supervised representation learning,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? A specific emitter identification method based on self-supervised representation learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.741018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ecc8c3ac-b2bf-474f-8b9c-f04efac1812b · outbound

This paper cites An empirical study of training self- supervised vision transformers,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? An empirical study of training self- supervised vision transformers,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.713568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c1584859-e8a1-44a1-8ca3-f2c743b9bf22 · outbound

This paper cites Dy- namically scaled temperature in self-supervised contrastive learning,.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Dy- namically scaled temperature in self-supervised contrastive learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:10:43.688569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a42dabf3-b19b-4b5e-bbde-9e87bdea085b · outbound

This paper cites Dynamically Scaled Temperature in Self-Supervised Contrastive Learning.

Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks? Dynamically Scaled Temperature in Self-Supervised Contrastive Learning

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:10:43.595859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation a5463d4f-f7a3-489e-90a6-851c457a93ac · inbound

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities cites this paper.

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks?

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:49.795636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.