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Paper Citation Record · LEDGER

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels

As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2605.22856.

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

pith.paper-citation-record.v1
2605.22856 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T00:05:57.796193Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T15:32:53.282167Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

  • verified exact16
  • verified fuzzy28
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ec82d4d-44ad-4604-b026-6e10a7931efa · outbound

This paper cites PilotWiMAE: Wireless channel pilots are all you need.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels PilotWiMAE: Wireless channel pilots are all you need

Reference 1

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raw_fallback, observed 2026-05-25T00:06:30.107977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:52943f5aa30b187dfc468e9ea965428639c13c3272e567ae67013f2b47308497

Observation aa2e2088-51ae-4615-bdaf-ee813991e221 · outbound

This paper cites LWM: A pre-trained wireless foundation model for universal feature extraction.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels LWM: A pre-trained wireless foundation model for universal feature extraction

Reference 2

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raw_fallback, observed 2026-05-25T00:06:30.124554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:5a4e77af1c7f06956caad7a60bd4cc4ee4cec5253adbde6067e21f94ada3d215

Observation 5a785e35-0c5f-4097-81c9-1d6c5802a17a · outbound

This paper cites A MIMO wireless channel foundation model via CIR- CSI consistency.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels A MIMO wireless channel foundation model via CIR- CSI consistency

Reference 3

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raw_fallback, observed 2026-05-25T00:06:30.120777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:4b22294be92033028a2abf1021c8f4cea980163403a0effbd32286e212255b04

Observation 4dec78c6-ab23-4754-b9df-665c1db4e443 · outbound

This paper cites CSI-MAE: A masked autoencoder-based channel foun- dation model.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels CSI-MAE: A masked autoencoder-based channel foun- dation model

Reference 4

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arxiv_id, observed 2026-05-25T00:06:29.143533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:99826d646f045aafa4657074b7838030103c348a03556036603600f73808f15a

Observation c1cb5775-3dca-4d2c-806f-eb664ec81cea · outbound

This paper cites WiFo: Wireless foundation model for channel prediction.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels WiFo: Wireless foundation model for channel prediction

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:51c9a8d3e435856668c934d005322690ce206b0c8a55b6c0db514cd6ba2138eb

Observation 0656309a-9c85-406e-95db-ba6c22c8803f · outbound

This paper cites LWM-Temporal: Sparse spatio-temporal attention for wireless channel representation learning.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels LWM-Temporal: Sparse spatio-temporal attention for wireless channel representation learning

Reference 6

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arxiv_id, observed 2026-05-25T00:06:29.191633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:c3f4174786ff8fd5604808ad143f559c5737e0c1e39574b5851573cb71d86759

Observation 799c0ca2-5e5a-4689-93f5-b2a179baa77d · outbound

This paper cites WirelessGPT: A generative foundation model for multi- task integrated sensing and communication.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels WirelessGPT: A generative foundation model for multi- task integrated sensing and communication

Reference 7

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raw_fallback, observed 2026-05-25T00:06:30.130796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:86b10809216d1a02814119404fa11d05e9c346ec346905c356fffb6b2238fa5b

Observation db677e52-f158-4611-bd59-54221a691b14 · outbound

This paper cites LLM4CP: Adapting large language models for channel prediction.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels LLM4CP: Adapting large language models for channel prediction

Reference 8

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raw_fallback, observed 2026-05-25T00:06:30.152682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:29ad695880fef9fa041d82dc4fa122223af3ac37abfdad9ee5d46b5b7d245990

Observation 9846f26d-3e90-4a49-abeb-2a97b54d7095 · outbound

This paper cites A multi-task foundation model for wireless channel representation using contrastive and masked autoencoder learning.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels A multi-task foundation model for wireless channel representation using contrastive and masked autoencoder learning

Reference 9

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raw_fallback, observed 2026-05-25T00:06:30.138691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:6bdda63cd9dcfaa1ebda8314644e314af6d517c9f22308c2f9bb7750b6ff25c6

Observation 6656563b-2fb3-44e1-a9cd-5c25572f3f61 · outbound

This paper cites WiFo-CF: Wireless Foundation Model for CSI Feedback.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels WiFo-CF: Wireless Foundation Model for CSI Feedback

Reference 10

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arxiv_id, observed 2026-05-25T00:06:29.183404Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:e1f4a33f8ceb8a0bc8db603242784e2c8b53fa2798f7d6508665b45fef4c5e04

Observation 5799996e-4071-407f-8085-e3ef20ac5b38 · outbound

This paper cites Filter-and-attend: Wireless channel foundation model with noise-plus-interference suppression structure.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Filter-and-attend: Wireless channel foundation model with noise-plus-interference suppression structure

Reference 11

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arxiv_id, observed 2026-05-25T00:06:29.151751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:f41bd601e4e30e5b5645a0a0a94580fcce24df1e3b2edce61ec2961cc1e1f27d

Observation 5aaf0fc3-80c4-4afe-8ca0-79a5387b2d27 · outbound

This paper cites A Wireless Foundation Model for Multi-Task Prediction.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels A Wireless Foundation Model for Multi-Task Prediction

Reference 12

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arxiv_id, observed 2026-05-25T00:06:29.126739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:9cc93d88ee36707c7120fa5935987674fa376452114d601b9e2f67da24f46441

Observation b5fad246-2dd3-4be9-b9f1-386f6636bcf2 · outbound

This paper cites Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks

Reference 13

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arxiv_id, observed 2026-05-25T00:06:29.135396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:48868b0db2962d05f534af37f9345d6881dccdebfb75909ae2fa456a32d01e52

Observation 357b343f-1331-4c13-b3d4-15149e6d819a · outbound

This paper cites Reducing pilots in channel estimation with predictive foundation models.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Reducing pilots in channel estimation with predictive foundation models

Reference 14

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arxiv_id, observed 2026-05-25T00:06:29.222913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:4257c68ddcc22e3fdfa0c8692a6b41244412e66e89938a7bd6a0e9a757bb6e49

Observation e88ee854-cf0d-4f30-836c-8ad471de4937 · outbound

This paper cites WiFo-2: a generalist foundation model unifies heterogeneous wireless system design.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels WiFo-2: a generalist foundation model unifies heterogeneous wireless system design

Reference 15

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local_arxiv, observed 2026-05-25T00:06:29.172811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:c4979f02c86f21ede0c8976dd5cf17ca20eca6b4361b1df237aac5b8823c1425

Observation 2baeeb4b-9714-4210-9b86-ece172486ed6 · outbound

This paper cites 6G WavesFM: A foundation model for sensing, communication, and localization.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels 6G WavesFM: A foundation model for sensing, communication, and localization

Reference 16

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:02ff16cdfb9ecbc1df3e9294a567f635fd301224a992ddec6d4ae02da45ac94f

Observation fa950b14-ffe6-4dfb-a2ff-9ddba4cf6276 · outbound

This paper cites LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 17

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arxiv_id, observed 2026-05-25T00:06:29.206437Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:d6dda872f2ab6d74e42b6aba410239634831d906ff57102f732e14c8070d8e44

Observation 55fec195-56c5-4a7f-9c3a-0e66f044f4a9 · outbound

This paper cites MUSE-FM: Multi-task environment-aware foundation model for wireless communications.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels MUSE-FM: Multi-task environment-aware foundation model for wireless communications

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:f689d5233821b435d0fcf8d4b318c3dcb8c2bf9f60d03a33a96ff692b9eedf60

Observation 3e17c2b2-8a48-4943-ba9b-47014c33bce7 · outbound

This paper cites OFDM channel estimation by singular value decom- position.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels OFDM channel estimation by singular value decom- position

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:84cd4128e48d8d46c61e8f7238bd34d92cf5c280ac9779c894cfebe21bfdbfea

Observation 549cbb4e-9339-4f46-9567-7776e26bdb80 · outbound

This paper cites Channel estimation techniques based on pilot arrange- ment in OFDM systems.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Channel estimation techniques based on pilot arrange- ment in OFDM systems

Reference 20

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:a8db9f87c123831b6b19b1c7b5858a3ac0ac7acc6101c96737f0f01857887517

Observation 7e753d40-3a7b-4f46-bf20-88067cc08d7f · outbound

This paper cites Benchmarking neural network robust- ness to common corruptions and perturbations.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Benchmarking neural network robust- ness to common corruptions and perturbations

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:ca70ffb7258eba71e671899e76f2a5c0630c4d1698f4c6ba1c23845ee8228355

Observation cb9bd40f-72f8-4cb0-b9b4-238b4d912098 · outbound

This paper cites Measuring robustness to natural distribution shifts in image classification.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Measuring robustness to natural distribution shifts in image classification

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:3fcafd9f6029b6807eb0716c569c9749b74dbbb9927203dcb52bcc8a1315e492

Observation dadf8df9-a284-4467-b9ee-14e25f1ce60e · outbound

This paper cites Attention is all you need.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Attention is all you need

Reference 23

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:f75f995170493077f98c1f153a7df405842fb0d345ae3ee5b7c6b803e589b306

Observation 4119c6e1-784a-4825-95b0-138a270477a3 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels An image is worth 16x16 words: Transformers for image recognition at scale

Reference 24

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:1f8d1de965f3db2bf9ec6711faa040bbd67b903a2010a52bd45c857ce568749f

Observation 17e9bd36-2c24-4c2b-b9c9-d4794c843981 · outbound

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

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:dacf77a52f70bc0a6422291896cb8ea4d532ca8c7eee16f55e29a1848bd15005

Observation c2b79b27-8f35-4d7c-97c4-c22cdec80f8c · outbound

This paper cites Masked autoencoders are scalable vision learners.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Masked autoencoders are scalable vision learners

Reference 26

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:77643e4e688c70f8001a480bcd12c94cd1e368165b9823a555622ce8e47eec5e

Observation 5c8a6e04-585f-4d01-b3cf-f618292aa5ac · outbound

This paper cites Scaling Laws for Neural Language Models.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Scaling Laws for Neural Language Models

Reference 27

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local_arxiv, observed 2026-05-25T00:06:29.165853Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:0de656554a3ceb6ba0b047b819f58a8f8f22db3639bcbd5fd308759b0f4982cc

Observation eb525507-e326-4a58-b381-b0d752faaaa3 · outbound

This paper cites Training compute-optimal large language models.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Training compute-optimal large language models

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:774b6a2fae7d8bc94ab329f7585acf33f0ab75a3cc8afb8c496fd16949dcd40a

Observation 888cc550-c7cb-437f-8dbb-a990b31f47db · outbound

This paper cites Scaling vision transformers.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Scaling vision transformers

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:a6a0004478c461c73e21d32a012b6afd7b80ccd017cd3b02c8e1215e2218d6b7

Observation 90688f0a-7be5-41ec-8365-601a601bbc4c · outbound

This paper cites NR; Physical Channels and Modulation.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels NR; Physical Channels and Modulation

Reference 30

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raw_fallback, observed 2026-05-25T00:06:30.096053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:f108aec7147dfbe9dd5eae0fda136471f61d2e48c751fb343284587e7a389da9

Observation 70d752c3-f142-4cdd-a668-87c45ef0f87b · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 31

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local_arxiv, observed 2026-05-25T00:06:29.102161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:2dfdc35b4928f6cc53d80f2eb233d39e05df2a371b4b7450f4e91d34b9163a9c

Observation 5fb9d714-87c3-4f53-ba87-a085c027a0e3 · outbound

This paper cites Characterization of randomly time-variant linear channels.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Characterization of randomly time-variant linear channels

Reference 32

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raw_fallback, observed 2026-05-25T00:06:30.178231Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:7cd5d81fd814ba0fe3301b11dbeb5e4233ebb26cee7d0aebbf9fceb4f486924f

Observation af57f58d-ea14-4dfd-ba50-6c3a0f126308 · outbound

This paper cites Chapter 1 - fundamentals of time-varying communication channels.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Chapter 1 - fundamentals of time-varying communication channels

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:b71b68e687437ef262d29e65152bf95284e736b9544c9e415661c7f221bd88f2

Observation 2c7ab083-1a79-451b-98d4-97ef2f14766d · outbound

This paper cites Self-supervised and invariant representations for wireless localization.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Self-supervised and invariant representations for wireless localization

Reference 34

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raw_fallback, observed 2026-05-25T00:06:30.186589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:cda69d8f37711673346e9b9b1561a29487b684275db0db43f55821f4e61efe1e

Observation 75ac9fd9-6a20-4f85-883f-a9c0c950e759 · outbound

This paper cites WirelessJEPA: A multi-antenna foundation model using spatio-temporal wireless latent predictions.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels WirelessJEPA: A multi-antenna foundation model using spatio-temporal wireless latent predictions

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:06:29.118512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:778432bdacc0a1025f91ca87d9490e78be1c961904a32857dd10a73ba4806dad

Observation dcb1c7a5-d199-4b5c-a631-7835fe52c029 · outbound

This paper cites How mask matters: Towards theoretical understandings of masked autoencoders.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels How mask matters: Towards theoretical understandings of masked autoencoders

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.073630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:2948a350a9a1be376706d8d454b411d923172e25e540e104d206094935e3d7cd

Observation e7b8c3f9-13cf-4fb1-9e39-9966bf011225 · outbound

This paper cites Is space-time attention all you need for video understanding?.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Is space-time attention all you need for video understanding?

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.070152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:cb247322f732b6eeb5b422f3f9308ceb86c79bb10065814c4dab949f868a960d

Observation a5d81431-a364-4382-b569-08b0b8240016 · outbound

This paper cites ViViT: A video vision transformer.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels ViViT: A video vision transformer

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.092171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:0c449e5a8d9f81f2300b16a5072288e5b534d2c10332f4b8732d5e5d21014053

Observation 88da41b3-8528-4124-9850-0993c4ff033a · outbound

This paper cites Computationally Efficient Neural Receivers via Axial Self-Attention.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Computationally Efficient Neural Receivers via Axial Self-Attention

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-15T02:21:57.874718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:e0dde9c1e5964945925fef4250310db325fe3010b4e2e04ef51d06349fb7412a

Observation b44021f2-f6eb-45de-92f0-b39f4906b61f · outbound

This paper cites Physics-informed transformer for multi-band channel frequency response reconstruction.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Physics-informed transformer for multi-band channel frequency response reconstruction

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:06:29.214265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:5a16c594971a05eabc78199610011be1177d9d5b48483376355a1bf4ee4829d7

Observation 82aaf507-3638-49da-8739-7591eb59910a · outbound

This paper cites Sionna rt: Technical report.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Sionna rt: Technical report

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:06:29.110208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:875667b1a8149373c6a45c5369407760990b66ca6bb97691d5134109a8aa41d6

Observation c2d025c7-ff63-4c51-aaa0-fada3df0a8e2 · outbound

This paper cites Study on channel model for frequencies from 0.5 to 100 GHz.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Study on channel model for frequencies from 0.5 to 100 GHz

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.083046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:666f53fd58926d5adf262265a8387bc068677216c4c7a947a751588059318407

Observation 4ae74401-5390-4ca9-a6ba-8c9009b17536 · outbound

This paper cites Physical layer procedures for data.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Physical layer procedures for data

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.112021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:38f229078a5bcff4340d1db36b8eba48c5d9dd9aa2b6675ad68d01554e7ca462

Observation d773ae57-79ab-43d6-be84-bae4036d6df9 · outbound

This paper cites The distance-weighted k-Nearest-Neighbor rule.

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels The distance-weighted k-Nearest-Neighbor rule

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T00:06:30.104229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T00:05:57.796193Z digest=sha256:6e5a29c069390d2f09e22a85de97e0eb3d7d4ac105d3b9145e35233de843fda0

Pith citing papers

Observation cd9faf04-4764-4453-9077-ac65f85aa9d2 · inbound

JEPA for AI-Native 6G: Predictive Representations and Open Challenges cites this paper.

JEPA for AI-Native 6G: Predictive Representations and Open Challenges PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-14T15:32:53.282167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:32:53.282167Z digest=sha256:2c5346a10a4eb850ae82c543c1ca5263f593ff18a220a5507f00ec6029755438