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Paper Citation Record · LEDGER

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 4 inbound Pith citation observations for arXiv:2506.14532.

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

pith.paper-citation-record.v1
2506.14532 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:24:50.132106Z

measured 33 of 33 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:40:22.265468Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T16:33:39.637911Z

Reference resolution

29 of 29 outbound references displayed

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  • unresolved7
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd5eb4cd-ac12-42bb-8734-2ab66701252c · outbound

This paper cites Mi llimeter wave communications for future mobile networks,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Mi llimeter wave communications for future mobile networks,

Reference 1

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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.

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Observation ec2c293b-f7d1-4a53-a978-8b5a066f8c04 · outbound

This paper cites A s urvey of beam management for mmwave and thz communications toward s 6g,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models A s urvey of beam management for mmwave and thz communications toward s 6g,

Reference 2

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

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Observation e5143b90-3d8c-4012-8d33-9a2a61fc5650 · outbound

This paper cites Deep learning for mmwave beam and blockage prediction using sub-6 ghz channels,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Deep learning for mmwave beam and blockage prediction using sub-6 ghz channels,

Reference 3

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

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Observation a0d7ffc9-5cb4-4820-9036-63d7afc7a99d · outbound

This paper cites Computer vision aided beam tr acking in A real-world millimeter wave deployment,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Computer vision aided beam tr acking in A real-world millimeter wave deployment,

Reference 4

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Source-reported events for the cited work

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Observation 2a2260be-59e6-474d-85cd-d4b2bb4b54e7 · outbound

This paper cites Radar aided 6G beam predic tion: Deep learning algorithms and real-world demonstration,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Radar aided 6G beam predic tion: Deep learning algorithms and real-world demonstration,

Reference 5

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Source-reported events for the cited work

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

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Observation 9f9c449d-52e9-43e7-b1a9-5363d931e551 · outbound

This paper cites LiDAR aided futur e beam prediction in real-world millimeter wave V2I communicatio ns,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models LiDAR aided futur e beam prediction in real-world millimeter wave V2I communicatio ns,

Reference 6

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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.

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Observation 5be5c806-a9fc-4f9c-8e25-f79970d2382d · outbound

This paper cites P osition-aided beam prediction in the real world: How useful GPS locations a ctually are?.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models P osition-aided beam prediction in the real world: How useful GPS locations a ctually are?

Reference 7

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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.

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Observation 72f4a3b7-b578-42e9-8e06-e5ce0b995b6d · outbound

This paper cites GPT-4 Technical Report.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models GPT-4 Technical Report

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:48.117848Z digest=sha256:a4f00bdc9d8284e9ab747ff49841e54d54a81447e63cd2d863e7a8fd09af381f

Observation 5184ca33-4120-489d-8720-5a08ce0dc788 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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Observation 90c9f01e-59e7-4240-9765-5cf48a780c7d · outbound

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

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models

Reference 10

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Observation e6cccef9-c565-42af-98a2-daf5c6aab758 · outbound

This paper cites Large l anguage models empower multimodal integrated sensing and communic ation,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Large l anguage models empower multimodal integrated sensing and communic ation,

Reference 11

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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.

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Observation 56e867be-1561-4113-b009-748c6c824763 · outbound

This paper cites Multimodal d eep learning empowered millimeter-wave beam prediction,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Multimodal d eep learning empowered millimeter-wave beam prediction,

Reference 12

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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.

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Observation b99ffa39-2da8-4f87-bacb-15c53ab735b7 · outbound

This paper cites Multimodal Deep Learning-Empowered Beam Prediction in Future THz ISAC Systems.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Multimodal Deep Learning-Empowered Beam Prediction in Future THz ISAC Systems

Reference 13

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Observation df176b4d-a0ea-41d9-b642-ac3c1bfc77d2 · outbound

This paper cites Se nsing- assisted high reliable communication: A transformer-base d beamforming Approach,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Se nsing- assisted high reliable communication: A transformer-base d beamforming Approach,

Reference 14

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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.

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Observation e686b91b-1cbe-448b-b256-9685915a2713 · outbound

This paper cites LIMA: Less is more for alignment,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models LIMA: Less is more for alignment,

Reference 15

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

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Observation 06550958-54c5-4028-bd88-2367710a4da3 · outbound

This paper cites ImageNet: A large-scale fierarchical image database,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models ImageNet: A large-scale fierarchical image database,

Reference 16

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

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Observation 7d9e2a09-b08b-4cfe-9698-fe3646aff5ed · outbound

This paper cites Deep residual learni ng for image recognition,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Deep residual learni ng for image recognition,

Reference 17

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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.

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Observation 8c7f79f0-15fd-4e78-983a-2476097ea66a · outbound

This paper cites High accuracy range estimation of FMCW lev el radar based on the phase of the zero-padded FFT,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models High accuracy range estimation of FMCW lev el radar based on the phase of the zero-padded FFT,

Reference 18

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Source-reported events for the cited work

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

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Observation 117439e1-3e36-4b9d-a9ad-c813020b889d · outbound

This paper cites Gradient-based learning applied to document recognition,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Gradient-based learning applied to document recognition,

Reference 19

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

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Observation 6afab59c-9fad-4de8-9136-14eeefc7e34b · outbound

This paper cites Multimodal alignment and fusion: A su rvey,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Multimodal alignment and fusion: A su rvey,

Reference 20

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Observation 0af35d52-1787-4a4d-ad09-bc30e1bb3c98 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Learning transferable visual models from natural language supervision,

Reference 21

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

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Observation 99618bce-01a2-46f1-bb36-2d6f4ef00868 · outbound

This paper cites DeepSense 6G: A large-scale r eal-world multi-modal sensing and communication dataset,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models DeepSense 6G: A large-scale r eal-world multi-modal sensing and communication dataset,

Reference 22

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

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Observation e31cebee-64b8-4bec-9f49-3c5ffdf0f741 · outbound

This paper cites Language models are unsupervised multitask learn- ers,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Language models are unsupervised multitask learn- ers,

Reference 23

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

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Observation e5c7f8ab-22b9-451a-a881-e4ea3996817c · outbound

This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 76b9abeb-edbc-485d-9b72-03cf12ada0f6 · outbound

This paper cites Long short-term mem ory,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Long short-term mem ory,

Reference 25

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Source-reported events for the cited work

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

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Observation 74a58bb5-52df-4a47-8573-0a882421938d · outbound

This paper cites Are transformers e ffective for time series forecasting?.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Are transformers e ffective for time series forecasting?

Reference 26

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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.

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Observation 37046302-6373-4f1f-acc8-d35c91cce22a · outbound

This paper cites Informer: Beyond efficient transformer for long sequence t ime-series Forecasting,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Informer: Beyond efficient transformer for long sequence t ime-series Forecasting,

Reference 27

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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.

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Observation 7802d9bd-0163-463b-b37b-5e05b10883dc · outbound

This paper cites Adam: A method for stochastic opt imization,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Adam: A method for stochastic opt imization,

Reference 28

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raw_fallback, observed 2026-08-07T00:24:50.674594Z

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.

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Observation 5eb057d7-48e9-4a0b-b074-aeb343004f16 · outbound

This paper cites Multi-modal transformer and reinforcement learning-bas ed beam man- agement,.

M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models Multi-modal transformer and reinforcement learning-bas ed beam man- agement,

Reference 29

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raw_fallback, observed 2026-08-07T00:24:50.491920Z

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.

source=pdf_text observed=2026-08-07T00:24:50.132106Z digest=sha256:9491376b5e7eb7a92daa4e170f99b21333b64ea621006fc068f11ab64a1b5054

Pith citing papers

Observation 1cf64bad-a523-42a2-a67e-945f815775d6 · inbound

Data-Free Knowledge Distillation for LiDAR-Aided Beam Tracking in MmWave Systems cites this paper.

Data-Free Knowledge Distillation for LiDAR-Aided Beam Tracking in MmWave Systems M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models

Reference 9

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no resolver link, observed 2026-08-04T15:40:22.265468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:40:22.265468Z digest=sha256:f4e722d7d395fb40e085b82e9baedef4f31a1b34f2e504f05f520c413b98a731

Observation e82aaa2a-95c8-4412-8f0e-a40203176bd6 · inbound

Topological sum rule for geometric phases of quantum gates cites this paper.

Topological sum rule for geometric phases of quantum gates M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models

Reference 13

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no resolver link, observed 2026-07-13T15:33:59.448352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T15:33:59.448352Z digest=sha256:ef8d6c72e9bb6f3d0aacc7221a52eac82d3f701eea3b5118d9529acfcc923017

Observation 48368cbe-0f95-45cf-9390-012488609407 · inbound

NF-TrackLLM: Joint Prediction of UAV Trajectory and Near-Field Beam for LAE XL-MIMO Systems cites this paper.

NF-TrackLLM: Joint Prediction of UAV Trajectory and Near-Field Beam for LAE XL-MIMO Systems M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models

Reference 8

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arxiv_id, observed 2026-06-29T16:33:39.639365Z

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.

source=pdf_text observed=2026-06-29T15:47:39.983216Z digest=sha256:3361391352f559d0a8559e42e062717bc8561df637858f08e2451febffba6a27

Observation 757e0fba-c084-49f2-a905-49dd6ea45fc1 · inbound

M3F-UAV: A Missing-Modality Multimodal Foundation Model for Low-Altitude Wireless Sensing cites this paper.

M3F-UAV: A Missing-Modality Multimodal Foundation Model for Low-Altitude Wireless Sensing M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models

Reference 21

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