Paper Citation Record · LEDGER

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

As of 22 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 5 inbound Pith citation observations for arXiv:2501.10630.

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

pith.paper-citation-record.v1
2501.10630 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:04:41.748256Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:03.391437Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:46:09.792436Z

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy16
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3878bbfd-de91-4a41-8263-bd623e874ab3 · outbound

This paper cites A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.976053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 91d7e6ec-115a-42b9-a47e-26192efb5f35 · outbound

This paper cites Massive MIMO: An Introduction,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Massive MIMO: An Introduction,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.962918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7b45a91-08d6-4182-9fee-49e8e4fdda15 · outbound

This paper cites An Overview of Massive MIMO: Benefits and Challenges,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback An Overview of Massive MIMO: Benefits and Challenges,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.949769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d7e9e00b-8e40-4a8c-8294-c7a31296d9fd · outbound

This paper cites An overview of limited feedback in wireless communi- cation systems,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback An overview of limited feedback in wireless communi- cation systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.937408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c5a9cff7-551a-4ffe-9e86-aa159d4ab4d7 · outbound

This paper cites From Denoising to Compressed Sensing,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback From Denoising to Compressed Sensing,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.924544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5634a3c9-570d-4f59-8e50-cb6397f07f6a · outbound

This paper cites Deep Learning for Massive MIMO CSI Feedback,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Deep Learning for Massive MIMO CSI Feedback,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.911889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 923bf3cc-7646-49a2-9c3d-f75b79d06c50 · outbound

This paper cites Overview of Deep Learning- Based CSI Feedback in Massive MIMO Systems,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Overview of Deep Learning- Based CSI Feedback in Massive MIMO Systems,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.899784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6ee9482c-4abc-4a37-a40a-d1ba9b4d73b3 · outbound

This paper cites DS-NLCsiNet: Exploiting Non- Local Neural Networks for Massive MIMO CSI Feedback,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback DS-NLCsiNet: Exploiting Non- Local Neural Networks for Massive MIMO CSI Feedback,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.888137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6ba96956-9bcd-4e7e-9d63-cfb3e017b101 · outbound

This paper cites Com- pressive Sampled CSI Feedback Method Based on Deep Learning for FDD Massive MIMO Systems,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Com- pressive Sampled CSI Feedback Method Based on Deep Learning for FDD Massive MIMO Systems,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.876678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e2117273-bb37-4ee8-9d7f-cba68c18ab76 · outbound

This paper cites Deep learning- based csi feedback for ris-aided massive mimo systems with time correlation,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Deep learning- based csi feedback for ris-aided massive mimo systems with time correlation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.864944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab64ba05-b751-429d-b16d-a9fd11487fdd · outbound

This paper cites Language Models are Unsupervised Multitask Learners,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Language Models are Unsupervised Multitask Learners,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.852027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d63e0de3-4526-4105-80d3-a44d45e03022 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T19:04:41.729331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ec3ee0-b8a5-44ea-b314-0f82f01dfa90 · outbound

This paper cites LLM4CP: Adapting Large Language Models for Channel Prediction,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback LLM4CP: Adapting Large Language Models for Channel Prediction,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.838719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 956b84e0-6f08-47cd-94bf-ed762c3ffc65 · outbound

This paper cites Attention Is All You Need,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback Attention Is All You Need,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.827376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 798d7570-88e2-44f6-afae-92da83a317f3 · outbound

This paper cites QuaDRiGa: A 3-D multi-cell Channel Model with Time Evolution for Enabling Virtual Field Trials,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback QuaDRiGa: A 3-D multi-cell Channel Model with Time Evolution for Enabling Virtual Field Trials,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.816217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2338b890-fcd1-4db5-b5ab-b491df572e2a · outbound

This paper cites NR; user equipment (UE) radio transmission and reception; Part 1: Range 1 Standalone (Release 17),.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback NR; user equipment (UE) radio transmission and reception; Part 1: Range 1 Standalone (Release 17),

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.803650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 43d6a155-4d9c-46e5-bdea-12e9bec7655f · outbound

This paper cites TransNet: Full Attention Network for CSI Feedback in FDD Massive MIMO System,.

Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback TransNet: Full Attention Network for CSI Feedback in FDD Massive MIMO System,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:04:41.791787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 9e8192e2-ad3a-4f3a-a1c6-d1096c387f2d · inbound

LLM4SG: Adapting Large Language Model for Scatterer Generation via Synesthesia of Machines cites this paper.

LLM4SG: Adapting Large Language Model for Scatterer Generation via Synesthesia of Machines Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:03.391437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 331dc49f-3656-496b-aba0-4cb325305c80 · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:55.689365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

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 63e83ebe-c812-46ec-87a0-25116c77ff55 · inbound

MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction cites this paper.

MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:09.794396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16c8890e-3ff0-4d91-83f9-ae5b787e69e3 · 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 Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:01:49.035323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.