Paper Citation Record · LEDGER

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning

As of 24 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2411.09849.

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

pith.paper-citation-record.v1
2411.09849 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:17:37.345493Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

12 of 12 outbound references displayed

verified exact0
verified fuzzy6
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afa57197-9942-4790-b7e2-1e6cd662db94 · outbound

This paper cites Self-supervised learning: Generative or contrastive,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Self-supervised learning: Generative or contrastive,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.285346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb249f6b-6595-49be-b633-f1c9e468b918 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.291277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c451d95-cbe8-4513-9290-0afe61ce5091 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.296240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db8c9ae1-a051-45fc-909e-61e501a2864d · outbound

This paper cites Self-supervised Pretraining of Visual Features in the Wild.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Self-supervised Pretraining of Visual Features in the Wild

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.302274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17ced4d3-eafd-45b8-9967-628a859bd1b4 · outbound

This paper cites An introduction to deep learning for the physical layer,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning An introduction to deep learning for the physical layer,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.307600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e1f984a-d010-43d8-865a-b51c396c26e3 · outbound

This paper cites Automatic modulation classifica- tion: A deep learning enabled approach,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Automatic modulation classifica- tion: A deep learning enabled approach,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.551941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 251ba160-118a-4b27-9b7a-bc8a50a94c23 · outbound

This paper cites Deep learning for beamspace channel es- timation in millimeter-wave massive mimo systems,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Deep learning for beamspace channel es- timation in millimeter-wave massive mimo systems,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.528144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5f45ecdb-b6bb-4c90-923d-5e202d85aa1c · outbound

This paper cites Waveform learning for next-generation wireless communication systems,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Waveform learning for next-generation wireless communication systems,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T20:17:37.325619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32feb45f-7376-4372-95c6-591ecbd780dc · outbound

This paper cites Large generative ai models for telecom: The next big thing?.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Large generative ai models for telecom: The next big thing?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.496569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f70e1ea9-aded-480f-a3ba-e6d050c59d2a · outbound

This paper cites Masked spectrogram prediction for self-supervised audio pre-training,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Masked spectrogram prediction for self-supervised audio pre-training,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.478361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 88092526-1d64-4885-bf4d-11f2bba06199 · outbound

This paper cites Spectrum sensing with deep learning to identify 5g and lte signals.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Spectrum sensing with deep learning to identify 5g and lte signals

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.459524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7a992576-9059-4a16-942d-5e3723bb18b4 · outbound

This paper cites Convolutional lstm network: A machine learning approach for precipita- tion nowcasting,.

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning Convolutional lstm network: A machine learning approach for precipita- tion nowcasting,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:37.439858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.