Paper Citation Record · LEDGER

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications

As of 17 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2506.21983.

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

pith.paper-citation-record.v1
2506.21983 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:22:10.382146Z

measured 30 of 30 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact3
verified fuzzy17
unresolved6
parse uncertain0
malformed identifier1
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bb30bdec-2efb-4356-b7f3-08c4174cd7dd · outbound

This paper cites ”Key focus areas and enabling technologies for 6G.” IEEE Communications Magazine 63.3 (2025): 84-91.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications ”Key focus areas and enabling technologies for 6G.” IEEE Communications Magazine 63.3 (2025): 84-91

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:38.403843Z

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 cbce11e5-0e2a-4137-95a2-70a9e17fa9d5 · outbound

This paper cites Study on Artificial Intelligence (AI)/Machine Learn- ing (ML) for NR Air Interface RAN,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Study on Artificial Intelligence (AI)/Machine Learn- ing (ML) for NR Air Interface RAN,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:38.254192Z

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 d87b0212-9fb1-4645-ae2e-df21477bde45 · outbound

This paper cites The Case for Cellular V2X for Safety and Cooperative Driving,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications The Case for Cellular V2X for Safety and Cooperative Driving,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:38.121635Z

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 dcc6aa31-dc39-4439-87f9-18ee3ef197b1 · outbound

This paper cites ”6G for vehicle-to-everything (V2X) commu- nications: Enabling technologies, challenges, and opportunities.” Proceed- ings of the IEEE 110.6 (2022): 712-734.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications ”6G for vehicle-to-everything (V2X) commu- nications: Enabling technologies, challenges, and opportunities.” Proceed- ings of the IEEE 110.6 (2022): 712-734

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:38.007616Z

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 a8d95c31-a135-495c-8092-abe68a643d63 · outbound

This paper cites O’Shea & J.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications O’Shea & J

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:07.647263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc0403c1-e10c-4c53-9dcb-9e9df180d438 · outbound

This paper cites Learning the MMSE channel estimator,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Learning the MMSE channel estimator,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.932534Z

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 930504fe-2d8c-4d5f-94b8-f7c7ec471d23 · outbound

This paper cites Deep learning-based channel estima- tion for beamspace mmWave massive MIMO systems,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Deep learning-based channel estima- tion for beamspace mmWave massive MIMO systems,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.838963Z

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 93bb0b77-e39e-4c70-8b11-cdf205a59671 · outbound

This paper cites Complex CNN-based equalization for communication signal,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Complex CNN-based equalization for communication signal,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.779138Z

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 db203cb0-5acc-4f42-9b82-c222dc8982a6 · outbound

This paper cites Shental & J.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Shental & J

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-06T22:22:34.232492Z

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 7b182603-d9c7-4275-89ec-2a1dc38b09a8 · outbound

This paper cites Michon, F.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Michon, F

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.715564Z

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 08e8c65c-61ac-4770-a28f-ac0e8b5f4e06 · outbound

This paper cites Cammerer, J.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Cammerer, J

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.657296Z

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 6e749940-e13e-4b74-8753-c748086cdac6 · outbound

This paper cites ComNet: Combination of deep learning and expert knowledge in OFDM receivers,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications ComNet: Combination of deep learning and expert knowledge in OFDM receivers,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.595570Z

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 c99f4a21-1f63-4b7a-b06d-8ec009b2b27b · outbound

This paper cites Model-driven deep learning for physical layer communications,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Model-driven deep learning for physical layer communications,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.533471Z

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 d9119aef-a135-4f8c-9efe-f827e2ee5c90 · outbound

This paper cites Learning to detect,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Learning to detect,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.439861Z

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 08de1e69-3ece-45f1-91a4-51a44db99ab2 · outbound

This paper cites Power of deep learning for channel es- timation and signal detection in OFDM systems,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Power of deep learning for channel es- timation and signal detection in OFDM systems,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.354446Z

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 7f7a952c-3ca1-43c9-aa43-378a88cbf38f · outbound

This paper cites an unresolved cited work.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Unresolved cited work

Reference 16

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T22:22:34.040260Z

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 cfb0645e-2587-4ce4-aa76-92d1e9769f72 · outbound

This paper cites Honkala, D.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Honkala, D

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T22:22:33.845801Z

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 deaba2ad-aa7a-4cee-b6c8-b436969b1e2e · outbound

This paper cites an unresolved cited work.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:09.328426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7a4de7c-3389-4197-b6aa-bcbd5af7c68d · outbound

This paper cites Akrout, A.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Akrout, A

Reference 19

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T22:22:33.590335Z

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 8bd202d0-8366-4228-a5f7-70f0dbd24570 · outbound

This paper cites Cammerer et al., ”A Neural Receiver for 5G NR Multi-User MIMO,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Cammerer et al., ”A Neural Receiver for 5G NR Multi-User MIMO,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:09.509617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8063ff5e-d129-41f0-a941-1a06db404674 · outbound

This paper cites Saleem, S.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Saleem, S

Reference 21

Resolution: malformed identifier; no resolver link, observed 2026-08-06T22:22:09.572487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe8a9a88-a520-4ba0-96e9-9f80d5728ce6 · outbound

This paper cites Deep Multi-modal Neural Receiver for 6G Vehicular Communication.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Deep Multi-modal Neural Receiver for 6G Vehicular Communication

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:22:10.751995Z

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 59d28f72-feaa-4923-8eb2-f6c91c2831a2 · outbound

This paper cites Novel Deep Neural OFDM Receiver Architectures for LLR Estimation.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Novel Deep Neural OFDM Receiver Architectures for LLR Estimation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:22:10.588299Z

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 87553802-a326-4d68-8192-2d84dfa7da09 · outbound

This paper cites an unresolved cited work.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:22:37.288598Z

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 bdac0ea1-e1a7-4d00-bff4-487ff30bb4a4 · outbound

This paper cites Neural enhanced belief propagation on factor graphs,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Neural enhanced belief propagation on factor graphs,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:37.158726Z

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 fc265655-2e68-41be-a98d-6e8d0348adda · outbound

This paper cites Sionna: An Open-Source Library for Next-Generation Physical Layer Research.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:10.037169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e2f94c-41ed-4afe-89de-3730c79b5089 · outbound

This paper cites Alkhateeb, G.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Alkhateeb, G

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:36.946746Z

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 cbfa306c-ee37-4788-947c-6a09a5a249a9 · outbound

This paper cites An Extensible Framework for Open Heterogeneous Collaborative Perception.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications An Extensible Framework for Open Heterogeneous Collaborative Perception

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:10.201159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a68ec9-7b5f-4004-b89e-ed93c7b2f734 · outbound

This paper cites ”nuscenes: A multimodal dataset for autonomous driving.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications ”nuscenes: A multimodal dataset for autonomous driving.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:36.588465Z

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 47ccf652-3b71-4230-a082-0b564d4be26d · outbound

This paper cites Technical Specification Group Services and System Aspects; Release description; Release 15,.

Learning-Based Hybrid Neural Receiver for 6G-V2X Communications Technical Specification Group Services and System Aspects; Release description; Release 15,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:22:34.502571Z

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

No inbound Pith citation observations are available.