Paper Citation Record · LEDGER

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 3 inbound Pith citation observations for arXiv:2506.06718.

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

pith.paper-citation-record.v1
2506.06718 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:56:03.184639Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:29:04.004885Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T03:24:12.823949Z

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy24
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d007fe4-55ea-419c-8d11-68e9d86a5e10 · outbound

This paper cites Robust automatic modulation classification in low signal to noise ratio,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Robust automatic modulation classification in low signal to noise ratio,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.721801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2f350bc5-dacd-4c85-bd38-a045f8e43b5c · outbound

This paper cites Deep learning-based channel estimation,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Deep learning-based channel estimation,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.051849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 044d5760-f3d0-4b7a-954a-7d768c868f44 · outbound

This paper cites Direction-of-arrival estimation based on deep neural networks with robustness to array imperfections,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Direction-of-arrival estimation based on deep neural networks with robustness to array imperfections,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.692180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8c1ec2a3-cdb7-4cba-badc-11952d2c1a37 · outbound

This paper cites Enhancing adaptive beamforming in 3-D space through self-improving neural network techniques,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Enhancing adaptive beamforming in 3-D space through self-improving neural network techniques,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.677475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3fe1e9dd-2519-4152-82bb-a54b90a6ebc4 · outbound

This paper cites Advances in machine learning-driven cognitive radio for wireless networks: A survey,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Advances in machine learning-driven cognitive radio for wireless networks: A survey,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.661533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e550f6f6-78de-4ac2-bea8-d5107d39badd · outbound

This paper cites Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.068395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98f33413-e849-4516-962d-bb138a56df54 · outbound

This paper cites Deep learning for B5G open radio access network: Evolution, survey, case studies, and challenges,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Deep learning for B5G open radio access network: Evolution, survey, case studies, and challenges,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.645270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 12154523-fd43-4260-a475-9f09d71980e5 · outbound

This paper cites Overcoming data limitations: A few-shot specific emitter identification method using self-supervised learning and adversarial augmentation,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Overcoming data limitations: A few-shot specific emitter identification method using self-supervised learning and adversarial augmentation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.629370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec4503e1-7d24-441b-983f-9d59d33f0943 · outbound

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

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-supervised RF signal representation learning for NextG signal clas- sification with deep learning,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.080584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4287ad38-a215-48c4-9cd4-f921c8ab98c6 · outbound

This paper cites A transformer-based contrastive semi-supervised learning framework for automatic modula- tion recognition,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G A transformer-based contrastive semi-supervised learning framework for automatic modula- tion recognition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.604740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation db6e0ead-27c0-468d-892f-a32670c407e8 · outbound

This paper cites Exploring self-supervised learning for radio signal recognition,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Exploring self-supervised learning for radio signal recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.589623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 924e1fc4-0c7e-4c3b-ba26-21d3ebd5b6f9 · outbound

This paper cites Robust mmWave beamforming by self- supervised hybrid deep learning,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Robust mmWave beamforming by self- supervised hybrid deep learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.574334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b657c297-034b-4584-87bd-c11154aadc30 · outbound

This paper cites Few-shot specific emitter identification using asymmetric masked auto-encoder,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Few-shot specific emitter identification using asymmetric masked auto-encoder,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.560260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8325a32d-50dd-4292-8fcc-ad60d23c4d60 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.100064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d0f85c2-749b-4b56-b9ed-adddae0c966d · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G BERT: Pre-training of deep bidirectional transformers for language understanding,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.542124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b624c8f1-f9e1-47e3-ad4a-4c06892ae5d8 · outbound

This paper cites WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.108601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28be3376-e10a-4f34-9b4d-b7e22d05055f · outbound

This paper cites 6G WavesFM: A Foundation Model for Sensing, Communication, and Localization.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G 6G WavesFM: A Foundation Model for Sensing, Communication, and Localization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.112903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7be53595-c56f-4757-acdf-e7fad87fef2c · outbound

This paper cites A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.117255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fb81367-c2e7-4c4f-b9f6-b5f2ab6fa522 · outbound

This paper cites Self-contrastive learning based semi-supervised radio modulation classification,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-contrastive learning based semi-supervised radio modulation classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.526876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation be9af4de-c191-4134-910f-992a738f9a4c · outbound

This paper cites MCLHN: Toward automatic modulation classification via masked contrastive learning with hard negatives,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G MCLHN: Toward automatic modulation classification via masked contrastive learning with hard negatives,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.512378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1cb7fda-33a9-4fb7-8195-39fbee08b18a · outbound

This paper cites Radar signal modulation recognition with self-supervised contrastive learning,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Radar signal modulation recognition with self-supervised contrastive learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.496895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8143fb76-af67-42e2-b0b3-c3cff8b2acbb · outbound

This paper cites GAF-MAE: A self- supervised automatic modulation classification method based on gramian angular field and masked autoencoder,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G GAF-MAE: A self- supervised automatic modulation classification method based on gramian angular field and masked autoencoder,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.482051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d74f95b-3dee-4836-a8ce-0120fa96d538 · outbound

This paper cites Leveraging Self-Supervised Learning for MIMO-OFDM Channel Representation and Generation.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Leveraging Self-Supervised Learning for MIMO-OFDM Channel Representation and Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.137828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf8e8ffd-a2a7-4d27-b9ed-5a97b6db339c · outbound

This paper cites Self-supervised contrastive learning for joint active and passive beamforming in RIS-assisted MU-MIMO systems,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-supervised contrastive learning for joint active and passive beamforming in RIS-assisted MU-MIMO systems,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.466500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cf1935e7-42d9-440f-a21d-94460a547f81 · outbound

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

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-supervised learning for enhancing angular resolution in automotive MIMO radars,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.452954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5a2d96e7-8ceb-4ffe-a597-1c0e09ef8588 · outbound

This paper cites Multi-task learning approach for mod- ulation and wireless signal classification for 5G and beyond: Edge deployment via model compression,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Multi-task learning approach for mod- ulation and wireless signal classification for 5G and beyond: Edge deployment via model compression,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.438435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 72230a52-1d7b-4280-a4e2-4da1b97896d5 · outbound

This paper cites Self-supervised radio representation learning: Can we learn multiple tasks?.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-supervised radio representation learning: Can we learn multiple tasks?

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.423622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a917e72e-8a77-4bee-be3d-c862106feec8 · outbound

This paper cites Building 6G Radio Foundation Models with Transformer Architectures.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Building 6G Radio Foundation Models with Transformer Architectures

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.157952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 321c4490-55e2-4ef4-9556-4311ded34001 · outbound

This paper cites Self-supervised radio pre-training: Toward foundational models for spectrogram learning,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Self-supervised radio pre-training: Toward foundational models for spectrogram learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.409511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5b97099c-a9a1-4143-8b3b-7a6e88480386 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G A simple framework for contrastive learning of visual representations,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.165962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b912723-9459-4b92-85b4-bd1e2a3a8dbf · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Momentum contrast for unsupervised visual representation learning,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:03.170022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c966851-1d58-4688-8c36-ef03f8a5133d · outbound

This paper cites Bootstrap your own latent a new approach to self-supervised learning,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Bootstrap your own latent a new approach to self-supervised learning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.376985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74ccf23b-2db2-488a-8650-db8878ee51d5 · outbound

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

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G An introduction to deep learning for the physical layer,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.363172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5fbc4fd0-b03f-43c7-b1a2-5b9178d213f3 · outbound

This paper cites Trust in 5G open RANs through machine learning: RF fingerprinting on the POWDER PAWR platform,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Trust in 5G open RANs through machine learning: RF fingerprinting on the POWDER PAWR platform,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.349378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1334c90-bbff-49e7-a683-6474b9dcb665 · outbound

This paper cites DeepBeam: Deep waveform learning for coordination-free beam management in mmWave networks,.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G DeepBeam: Deep waveform learning for coordination-free beam management in mmWave networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:56:03.333975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation dd1c2dcb-50fd-481f-87a6-a3ba016d2b1a · inbound

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

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:47.516217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12e679fa-6cc2-4d65-a24b-254bf4289fce · inbound

Fast Wireless Foundation Models with Early-Exits cites this paper.

Fast Wireless Foundation Models with Early-Exits IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T03:24:12.825322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 16102a72-3792-4c3d-8230-4d02c2a76822 · inbound

Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications cites this paper.

Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T23:29:04.004885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.