Paper Citation Record · LEDGER

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

As of 17 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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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.