Paper Citation Record · LEDGER

Computationally Efficient Neural Receivers via Axial Self-Attention

As of 17 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2510.12941.

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

pith.paper-citation-record.v1
2510.12941 v3

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:53:05.822637Z

measured 22 of 22 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T00:05:57.796193Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T00:06:29.154894Z

Reference resolution

21 of 21 outbound references displayed

verified exact0
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a2a0f99-ed02-4ec9-a9e9-5dfce76ccf36 · outbound

This paper cites Axial Attention in Multidimensional Transformers.

Computationally Efficient Neural Receivers via Axial Self-Attention Axial Attention in Multidimensional Transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:02.926949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0a9658d-403d-4831-8277-5decd6216ce7 · outbound

This paper cites A Tale of Two Mobile Generations: 5G-Advanced and 6G in 3GPP Release 20,.

Computationally Efficient Neural Receivers via Axial Self-Attention A Tale of Two Mobile Generations: 5G-Advanced and 6G in 3GPP Release 20,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.056528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3cd29a8-1a52-43ee-8d53-d459dcac562a · outbound

This paper cites Industrial Viewpoints on RAN Technologies for 6G.

Computationally Efficient Neural Receivers via Axial Self-Attention Industrial Viewpoints on RAN Technologies for 6G

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.220827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc9ed83-444e-400f-aee5-1421f181244a · outbound

This paper cites DeepRx: Fully Convolutional Deep Learning Receiver,.

Computationally Efficient Neural Receivers via Axial Self-Attention DeepRx: Fully Convolutional Deep Learning Receiver,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.378398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c41ae14-1c7f-491b-bf51-5f1c2a04ccaa · outbound

This paper cites End-to-End Learning for OFDM: From Neural Receivers to Pilotless Communication,.

Computationally Efficient Neural Receivers via Axial Self-Attention End-to-End Learning for OFDM: From Neural Receivers to Pilotless Communication,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.578826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6266ec12-3341-4bd0-be03-a3c95dc3e123 · outbound

This paper cites A Neural Receiver for 5G NR Multi-User MIMO,.

Computationally Efficient Neural Receivers via Axial Self-Attention A Neural Receiver for 5G NR Multi-User MIMO,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.744885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ecf3e6-58af-42b3-ae17-8b436a0fcb51 · outbound

This paper cites DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transfor- mations,.

Computationally Efficient Neural Receivers via Axial Self-Attention DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transfor- mations,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.819704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cd2cb73-98d1-4a28-a99d-591f6ed5af33 · outbound

This paper cites Efficient Quantization- Aware Neural Receivers: Beyond Post-Training Quantization,.

Computationally Efficient Neural Receivers via Axial Self-Attention Efficient Quantization- Aware Neural Receivers: Beyond Post-Training Quantization,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:03.998149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95331c65-7ffc-4a02-9693-15aaa5607377 · outbound

This paper cites Efficient Deep Neural Receiver with Post-Training Quantization,.

Computationally Efficient Neural Receivers via Axial Self-Attention Efficient Deep Neural Receiver with Post-Training Quantization,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.147739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7160d77d-9bf3-425c-8605-c9df5c44eb8b · outbound

This paper cites Attention is all you need,.

Computationally Efficient Neural Receivers via Axial Self-Attention Attention is all you need,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.281576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37e87d2c-90aa-4775-9163-77b76df83b73 · outbound

This paper cites A Unified Transformer Architecture for Low-Latency and Scalable Wireless Signal Processing.

Computationally Efficient Neural Receivers via Axial Self-Attention A Unified Transformer Architecture for Low-Latency and Scalable Wireless Signal Processing

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.397298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77fbe6e3-c3d8-4bdc-96bd-2ffdf9cc9cf6 · outbound

This paper cites Attention neural network for downlink cell-free massive mimo power control,.

Computationally Efficient Neural Receivers via Axial Self-Attention Attention neural network for downlink cell-free massive mimo power control,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.494890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f153233-6464-47cf-aa8b-d694dad89ff7 · outbound

This paper cites Pilot Contamination Aware Transformer for Downlink Power Control in Cell-Free Massive MIMO Networks.

Computationally Efficient Neural Receivers via Axial Self-Attention Pilot Contamination Aware Transformer for Downlink Power Control in Cell-Free Massive MIMO Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.651061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e656409c-9b1d-41f2-931d-8078fc4f12e5 · outbound

This paper cites Pilot contamination-aware graph attention network for power control in cfm- mimo,.

Computationally Efficient Neural Receivers via Axial Self-Attention Pilot contamination-aware graph attention network for power control in cfm- mimo,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.768568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d3e3033-6752-4cb0-bca3-f4eca8422e87 · outbound

This paper cites Study on channel model for frequencies from 0.5 to 100 GHz,.

Computationally Efficient Neural Receivers via Axial Self-Attention Study on channel model for frequencies from 0.5 to 100 GHz,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:04.912301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b21a8efe-342c-449d-bf94-8738ad3a9fe1 · outbound

This paper cites Bit-Metric Decoding Rate in Multi-User MIMO Systems: Theory,.

Computationally Efficient Neural Receivers via Axial Self-Attention Bit-Metric Decoding Rate in Multi-User MIMO Systems: Theory,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.080840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdbf7194-1970-4cf7-a835-532260a1d269 · outbound

This paper cites Deep Residual Learning for Image Recognition,.

Computationally Efficient Neural Receivers via Axial Self-Attention Deep Residual Learning for Image Recognition,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.228073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54f6a6e2-2891-4f9a-b34f-c321006fe2ca · outbound

This paper cites Layer Normalization.

Computationally Efficient Neural Receivers via Axial Self-Attention Layer Normalization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.349150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7380d077-a842-4908-9924-a01311bffaca · outbound

This paper cites Hoydis, S.

Computationally Efficient Neural Receivers via Axial Self-Attention Hoydis, S

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.559490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5eebc13-72f2-47c8-b77f-a1592023d7c2 · outbound

This paper cites Bishop,Deep Learning F oundations and Concepts, Springer, 2023.

Computationally Efficient Neural Receivers via Axial Self-Attention Bishop,Deep Learning F oundations and Concepts, Springer, 2023

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.658320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f8e0d13-6a19-4c23-a944-a53cf7f740a9 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Computationally Efficient Neural Receivers via Axial Self-Attention Adam: A Method for Stochastic Optimization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T09:53:05.822637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 88da41b3-8528-4124-9850-0993c4ff033a · inbound

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

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Computationally Efficient Neural Receivers via Axial Self-Attention

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-15T02:21:57.874718Z

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.