Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 10 inbound Pith citation observations for arXiv:2507.05121.

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

pith.paper-citation-record.v1
2507.05121 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:37:33.293090Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T14:29:39.922126Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:08:43.169828Z

Reference resolution

49 of 49 outbound references displayed

verified exact0
verified fuzzy38
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50ece9e1-4b38-49ea-8344-d5ca96398403 · outbound

This paper cites 6G takes shape,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks 6G takes shape,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.721116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 183202e3-7554-41b5-b37a-41c78213ab2a · outbound

This paper cites Future technology trends of terrestrial international mobile telecommunications systems towards 2030 and beyond,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Future technology trends of terrestrial international mobile telecommunications systems towards 2030 and beyond,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.711672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b650f5bb-e972-4e8e-b92f-e9b1c9fc916f · outbound

This paper cites The roadmap to 6G: AI empowered wireless networks,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks The roadmap to 6G: AI empowered wireless networks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.157422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77ff4e6c-f4c7-440a-9edc-537fd3338c4f · outbound

This paper cites Views on 6G Radio,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Views on 6G Radio,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.697763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c2fe4cba-40f8-4e85-9550-e4756fc7b5d0 · outbound

This paper cites Advanced deep learning models for 6G: Overview, opportunities, and challenges,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Advanced deep learning models for 6G: Overview, opportunities, and challenges,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.689869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcb65978-599b-414b-988b-04c6da59f232 · outbound

This paper cites Towards explainable AI for channel estimation in wireless communications,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Towards explainable AI for channel estimation in wireless communications,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.681166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0875dda1-38de-4d1d-a9e8-8c369ccdc1e3 · outbound

This paper cites Massive MIMO channel prediction: Kalman filtering vs. machine learning,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Massive MIMO channel prediction: Kalman filtering vs. machine learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.672757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1d84ba7-c4ba-46b7-af71-929f5943f2b3 · outbound

This paper cites Overview of deep learning- based CSI feedback in massive MIMO systems,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Overview of deep learning- based CSI feedback in massive MIMO systems,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.172909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbf8b0bf-2c51-4cb4-861b-76301ca202c3 · outbound

This paper cites AI empowered channel semantic acquisition for 6G integrated sensing and communication networks,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks AI empowered channel semantic acquisition for 6G integrated sensing and communication networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.659864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31529b15-824b-48d9-899a-08ed2f910b63 · outbound

This paper cites Twenty- five years of advances in beamforming: From convex and nonconvex op- timization to learning techniques,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Twenty- five years of advances in beamforming: From convex and nonconvex op- timization to learning techniques,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.651835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 58abb496-233f-4f26-93bc-2a59a4ac649b · outbound

This paper cites AI/ML for beam management in 5G-Advanced: A standardization perspective,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks AI/ML for beam management in 5G-Advanced: A standardization perspective,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.643646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a5e25a8-6b09-4fce-9c9f-a8873249d268 · outbound

This paper cites 5G NR positioning enhancements in 3GPP Release-18,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks 5G NR positioning enhancements in 3GPP Release-18,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.635531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61d8113a-4af2-4b16-9a9c-7c8bba41c9bb · outbound

This paper cites Rethinking bias- variance trade-off for generalization of neural networks,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Rethinking bias- variance trade-off for generalization of neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.627569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 29a6fef3-3a71-44d0-b12a-138302619633 · outbound

This paper cites A Survey of Large Language Models.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks A Survey of Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.190270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 967f152c-305e-417a-924c-bd46601ab868 · outbound

This paper cites Prompt-Enabled Large AI Models for CSI Feedback.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Prompt-Enabled Large AI Models for CSI Feedback

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.193341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a856e9a2-a340-4a2d-b6bc-137c9e3cda8c · outbound

This paper cites Large Wireless Model (LWM): A Foundation Model for Wireless Channels.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Large Wireless Model (LWM): A Foundation Model for Wireless Channels

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.196544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95b1ba78-d92d-4faa-ac87-53056a40917d · outbound

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

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks LLM4CP: Adapting large language models for channel prediction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.619515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e44b21ee-0c5d-467e-a1b0-f15045aae727 · outbound

This paper cites Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.202262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e2fe37a-d553-49ff-8570-0efa0cdeda22 · outbound

This paper cites BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.205351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65a324b6-9510-41fe-a153-0306eb4a6304 · outbound

This paper cites Port-LLM: A Port Prediction Method for Fluid Antenna based on Large Language Models.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Port-LLM: A Port Prediction Method for Fluid Antenna based on Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.208562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f3680bd-bf1f-49e8-b52b-bc6702aea4c0 · outbound

This paper cites Large Language Model Enabled Multi-Task Physical Layer Network.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Large Language Model Enabled Multi-Task Physical Layer Network

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.211716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6f1e6d4-5ac0-4aab-812d-b44b3533bc81 · outbound

This paper cites Deep transfer learning for gesture recognition with WiFi signals,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep transfer learning for gesture recognition with WiFi signals,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.611366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 26cc4aa3-44c5-4eb1-9c7e-3dd02cea12c2 · outbound

This paper cites U-shape networks are unified backbones for human action understanding from Wi-Fi signals,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks U-shape networks are unified backbones for human action understanding from Wi-Fi signals,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.603273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f782fd89-4429-4e93-bfd3-489841592028 · outbound

This paper cites Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.595037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f63d1516-e52c-4cff-85e6-e13566a78137 · outbound

This paper cites Deep denoising neural network assisted compressive channel estimation for mmwave intelligent reflecting surfaces,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep denoising neural network assisted compressive channel estimation for mmwave intelligent reflecting surfaces,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.586758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2297936-0261-43d2-affa-7b2084f506d8 · outbound

This paper cites Image super-resolution using deep convolutional networks,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Image super-resolution using deep convolutional networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.577568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8b24c2fb-58a7-4659-909b-af1b2ece01b4 · outbound

This paper cites Deep learning for super- resolution channel estimation in reconfigurable intelligent surface aided systems,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep learning for super- resolution channel estimation in reconfigurable intelligent surface aided systems,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.569323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e232f375-19c5-4c4f-926a-ff9fcfad625c · outbound

This paper cites You only look once: Unified, real-time object detection,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks You only look once: Unified, real-time object detection,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.559417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 84b77269-9f04-4e7b-845d-5fbd2b1fd05a · outbound

This paper cites Deep learning based fast downlink channel reconstruction for FDD massive MIMO systems,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep learning based fast downlink channel reconstruction for FDD massive MIMO systems,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.550449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd10b5d5-fa2c-4f2f-b121-e6605b741539 · outbound

This paper cites A novel dual-driven channel estimation scheme for spatially non-stationary fading environments,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks A novel dual-driven channel estimation scheme for spatially non-stationary fading environments,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.540924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a1b2e6eb-d140-4407-95e1-1e4d115f1455 · outbound

This paper cites Deep learning based user grouping for FD-MIMO systems exploiting statistical channel state information,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep learning based user grouping for FD-MIMO systems exploiting statistical channel state information,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.531553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5aec5241-7cf0-4013-877a-7622c9a4fe29 · outbound

This paper cites ImageNet classification with deep convolutional neural networks,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks ImageNet classification with deep convolutional neural networks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.522113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 01012acf-6d2e-4845-a7bb-97ff97d78da3 · outbound

This paper cites Convolutional neural networks based indoor Wi-Fi localization with a novel kind of CSI images,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Convolutional neural networks based indoor Wi-Fi localization with a novel kind of CSI images,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.512665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e4f5142f-4312-4c74-8876-24b45734634c · outbound

This paper cites Deep convolutional neural networks for indoor localization with CSI images,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep convolutional neural networks for indoor localization with CSI images,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.503748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3efc1ecc-5cb4-48f7-8259-775072401d9e · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Very deep convolutional networks for large-scale image recognition,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.494642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8babb551-38c1-4448-9b5d-d4285532a758 · outbound

This paper cites Medical image segmentation review: The success of U-Net,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Medical image segmentation review: The success of U-Net,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.485876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d3c0416a-c58f-4a73-8b0e-8feb877fc9ec · outbound

This paper cites Deep residual learning for image recognition,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Deep residual learning for image recognition,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.257151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4be43a36-3aa6-47bb-9539-50848e9f34d5 · outbound

This paper cites SrcSense: Robust WiFi-based motion source recognition via signal-informed deep learning,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks SrcSense: Robust WiFi-based motion source recognition via signal-informed deep learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.472242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1368e9f5-3678-464e-a671-0e59a1ad36bd · outbound

This paper cites DeepSpaceYoloDataset: Annotated astronomical images captured with smart telescopes,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks DeepSpaceYoloDataset: Annotated astronomical images captured with smart telescopes,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.463147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8df3c968-5774-47bc-a201-fa747c53710a · outbound

This paper cites DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:33.266123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f9b8c98-c2de-4a4e-b13d-640c0b2d4503 · outbound

This paper cites Weight distillation: Transferring the knowledge in neural network parameters,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Weight distillation: Transferring the knowledge in neural network parameters,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.454640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 89caa75f-01ac-43b2-a83a-b7abd4bea3cd · outbound

This paper cites A ConvNet for the 2020s,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks A ConvNet for the 2020s,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.445502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c897c537-ab17-499e-99af-8add7d16eeca · outbound

This paper cites Newtonized orthog- onal matching pursuit: Frequency estimation over the continuum,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Newtonized orthog- onal matching pursuit: Frequency estimation over the continuum,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.435863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae985f85-b3b3-4263-af36-94b2cb0752f1 · outbound

This paper cites A survey on behavior recognition using WiFi channel state information,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks A survey on behavior recognition using WiFi channel state information,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.425801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f09a075c-bd22-4880-8111-82c52a224620 · outbound

This paper cites CSI- StripeFormer: Exploiting stripe features for CSI compression in massive MIMO system,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks CSI- StripeFormer: Exploiting stripe features for CSI compression in massive MIMO system,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.416309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 950087f8-c24b-45df-957a-efa01e6cb76c · outbound

This paper cites CSWin transformer: A general vision transformer backbone with cross-shaped windows,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks CSWin transformer: A general vision transformer backbone with cross-shaped windows,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.407416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b1ded02e-270b-4482-8311-ec6ecbf9c6c9 · outbound

This paper cites CompFi: Partially con- nected neural network using complex CSI data for indoor localization,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks CompFi: Partially con- nected neural network using complex CSI data for indoor localization,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.398695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 86777378-7c19-471d-9f90-5bfb0abfa7fa · outbound

This paper cites Recurrent Conformer for WiFi activity recognition,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Recurrent Conformer for WiFi activity recognition,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.389381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 44ff3984-77b8-459c-ab77-087085935135 · outbound

This paper cites Searching for MobileNetV3,.

LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks Searching for MobileNetV3,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:33.378918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation c7683a3e-0ae5-418c-82ca-66c963792b46 · inbound

AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G cites this paper.

AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:01:49.042925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 868a0263-d1a3-42d2-b468-e7fccd76d3d2 · inbound

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models cites this paper.

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:06:07.505349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c6c6b4a-6685-4fe2-8af7-a8a4e8baa5e8 · inbound

SPA-MAE: A Physics-Guided CSI Foundation Model for Wireless Physical Layer cites this paper.

SPA-MAE: A Physics-Guided CSI Foundation Model for Wireless Physical Layer LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-20T02:07:58.902599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels cites this paper.

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

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-25T00:06:29.206437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6b152c13-8798-4d55-b19b-a875c680717a · inbound

ComHymba: Low-Complexity Domain-Informed Foundation Model for Wireless Communications cites this paper.

ComHymba: Low-Complexity Domain-Informed Foundation Model for Wireless Communications LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-25T03:55:19.941070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 05a91558-0a1e-42f0-b05e-95d16712867b · inbound

Disruption of a Giant: Spectroscopic Identification of Members in the Periphery and Tidal Tails of $\omega$ Centauri cites this paper.

Disruption of a Giant: Spectroscopic Identification of Members in the Periphery and Tidal Tails of $\omega$ Centauri LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-12T16:09:56.350349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d108222-1bc7-4a3b-ba13-e762564f749f · inbound

SpikeWFM: Spiking-Aided Wireless Foundation Model for Robust Channel Prediction cites this paper.

SpikeWFM: Spiking-Aided Wireless Foundation Model for Robust Channel Prediction LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T15:03:31.750301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c31a3f0-48a9-45df-ae1a-fbe6593839c6 · inbound

Foundation Models for Wireless Communications: From PHY Intelligence to Network Autonomy cites this paper.

Foundation Models for Wireless Communications: From PHY Intelligence to Network Autonomy LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:47:03.878680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 46366245-392d-4527-b0f0-b2730c2f2c0c · inbound

Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G cites this paper.

Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:08:43.171345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cdd71a45-e753-4f37-b42a-8c05cd075116 · inbound

Cross-System Neural Precoder: Exploiting Structural Consistency for Fast Adaptation cites this paper.

Cross-System Neural Precoder: Exploiting Structural Consistency for Fast Adaptation LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-30T14:29:39.922126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.