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Paper Citation Record · LEDGER

Joint Detection and Decoding: A Graph Neural Network Approach

As of 15 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2501.08871.

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

pith.paper-citation-record.v1
2501.08871 v3

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:21:17.667655Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

69 of 69 outbound references displayed

  • verified exact0
  • verified fuzzy60
  • unresolved9
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d13b8e7e-ad8f-4992-a4f0-59d36bdfd937 · outbound

This paper cites Graph Neural Network-Based Joint Equalization and Decoding,.

Joint Detection and Decoding: A Graph Neural Network Approach Graph Neural Network-Based Joint Equalization and Decoding,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 291a00a9-d655-4feb-a219-8044e80e0994 · outbound

This paper cites Proakis, Digital Communications.

Joint Detection and Decoding: A Graph Neural Network Approach Proakis, Digital Communications

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c64f99c4-f8af-475a-8071-02ffc381da2d · outbound

This paper cites Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts,.

Joint Detection and Decoding: A Graph Neural Network Approach Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8fb7a2bf-e907-4360-83da-855bbc900682 · outbound

This paper cites Multilayer perceptron structures applied to adaptive equalisers for data communications,.

Joint Detection and Decoding: A Graph Neural Network Approach Multilayer perceptron structures applied to adaptive equalisers for data communications,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a83b299d-ca33-410a-bb8c-dac5c58464d2 · outbound

This paper cites Model-based Deep Learning,.

Joint Detection and Decoding: A Graph Neural Network Approach Model-based Deep Learning,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 53d10b60-d45b-4d3c-b0e9-806304b1495a · outbound

This paper cites Extrinsic Neural Network Equalizer for Channels with High Inter-Symbol-Interference,.

Joint Detection and Decoding: A Graph Neural Network Approach Extrinsic Neural Network Equalizer for Channels with High Inter-Symbol-Interference,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b3925886-475a-4c1e-afc9-a9b0f00a47d1 · outbound

This paper cites Joint neural network equalizer and decoder,.

Joint Detection and Decoding: A Graph Neural Network Approach Joint neural network equalizer and decoder,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation bfab18a4-3986-405e-b0d4-8489068c40a3 · outbound

This paper cites Using recurrent neu- ral networks for adaptive communication channel equalization,.

Joint Detection and Decoding: A Graph Neural Network Approach Using recurrent neu- ral networks for adaptive communication channel equalization,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.403006Z digest=sha256:700af25091243b657c994a215197ce310a0e2eacaecc90b02634f1499601cb71

Observation 5dc10653-ecba-49ed-8265-43e3b15b29e1 · outbound

This paper cites Neural Network Detection of Data Sequences in Communication Systems,.

Joint Detection and Decoding: A Graph Neural Network Approach Neural Network Detection of Data Sequences in Communication Systems,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 11ff3eab-53af-49b0-bd9b-2cd3e9bb5068 · outbound

This paper cites Neural network-based successive interference cancellation for non-linear bandlimited channels,.

Joint Detection and Decoding: A Graph Neural Network Approach Neural network-based successive interference cancellation for non-linear bandlimited channels,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 263788aa-3435-4991-abf6-9fed1cfb3978 · outbound

This paper cites Optimal decoding of linear codes for minimizing symbol error rate (corresp.),.

Joint Detection and Decoding: A Graph Neural Network Approach Optimal decoding of linear codes for minimizing symbol error rate (corresp.),

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ea3db6bf-d0db-497d-9526-55d414bb36f7 · outbound

This paper cites Data-driven factor graphs for deep symbol detection,.

Joint Detection and Decoding: A Graph Neural Network Approach Data-driven factor graphs for deep symbol detection,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c6fb3963-2f0d-469a-b069-f88db516165e · outbound

This paper cites Lower Bounds on Error Probability in the Presence of Large Intersymbol Interference,.

Joint Detection and Decoding: A Graph Neural Network Approach Lower Bounds on Error Probability in the Presence of Large Intersymbol Interference,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f0a206c7-8fa8-4a77-9422-11e63d815583 · outbound

This paper cites Adaptive Maximum-Likelihood Receiver for Carrier- Modulated Data-Transmission Systems,.

Joint Detection and Decoding: A Graph Neural Network Approach Adaptive Maximum-Likelihood Receiver for Carrier- Modulated Data-Transmission Systems,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cfd7afbe-a8e9-47f2-ad36-af77c6654806 · outbound

This paper cites Factor graphs and the sum- product algorithm,.

Joint Detection and Decoding: A Graph Neural Network Approach Factor graphs and the sum- product algorithm,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 66432290-4be0-4299-acc9-87eca13e386e · outbound

This paper cites On the application of factor graphs and the sum-product algorithm to ISI channels,.

Joint Detection and Decoding: A Graph Neural Network Approach On the application of factor graphs and the sum-product algorithm to ISI channels,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 11966095-6b60-444c-aaaa-d495efe25969 · outbound

This paper cites SISO Detection Over Linear Channels With Linear Complexity in the Number of Interferers,.

Joint Detection and Decoding: A Graph Neural Network Approach SISO Detection Over Linear Channels With Linear Complexity in the Number of Interferers,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7450e044-4750-48f7-84c5-4b645429cdc7 · outbound

This paper cites A Novel Sum-Product Detection Algorithm for Faster-Than-Nyquist Signaling: A Deep Learning Ap- proach,.

Joint Detection and Decoding: A Graph Neural Network Approach A Novel Sum-Product Detection Algorithm for Faster-Than-Nyquist Signaling: A Deep Learning Ap- proach,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3d9c7ef6-17fe-41ee-ac15-36d9d44399d0 · outbound

This paper cites Low-Complexity Near-Optimum Symbol Detection Based on Neural Enhancement of Factor Graphs,.

Joint Detection and Decoding: A Graph Neural Network Approach Low-Complexity Near-Optimum Symbol Detection Based on Neural Enhancement of Factor Graphs,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 093fb33b-f888-4653-b1d8-d5f3c23e5e77 · outbound

This paper cites Learning to decode linear codes using deep learning,.

Joint Detection and Decoding: A Graph Neural Network Approach Learning to decode linear codes using deep learning,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b70b955e-9f22-4dd5-a090-5f4b6924d3a8 · outbound

This paper cites The graph neural network model,.

Joint Detection and Decoding: A Graph Neural Network Approach The graph neural network model,

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2fa65752-241b-4914-a934-1f267f93f071 · outbound

This paper cites Factor graph neural networks,.

Joint Detection and Decoding: A Graph Neural Network Approach Factor graph neural networks,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3fb32879-a395-444c-ae38-d05e3687be6a · outbound

This paper cites Neural Enhanced Belief Propagation on Factor Graphs,.

Joint Detection and Decoding: A Graph Neural Network Approach Neural Enhanced Belief Propagation on Factor Graphs,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 48ee55bb-3bf8-4a0c-92ae-3dacbba621e3 · outbound

This paper cites Graph Neural Networks for Channel Decoding,.

Joint Detection and Decoding: A Graph Neural Network Approach Graph Neural Networks for Channel Decoding,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8556d157-d060-4ef9-bd3c-ae836337e728 · outbound

This paper cites Graph Neural Networks for Massive MIMO Detection.

Joint Detection and Decoding: A Graph Neural Network Approach Graph Neural Networks for Massive MIMO Detection

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 814bb7e9-b896-4154-9cf1-763a5b4ee916 · outbound

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

Joint Detection and Decoding: A Graph Neural Network Approach A Neural Receiver for 5G NR Multi-User MIMO,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation bd4c715d-9ba9-4d13-82b3-61e1be8134bd · outbound

This paper cites Graph Neural Network Aided MU-MIMO Detectors,.

Joint Detection and Decoding: A Graph Neural Network Approach Graph Neural Network Aided MU-MIMO Detectors,

Reference 27

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no resolver link, observed 2026-08-10T20:21:17.477409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.477409Z digest=sha256:cc2bf35f924b37e0aa5ee956e4d6d224280bedb1136e9063ebde751a06795356

Observation 50590b76-2f28-4454-a235-200027093aa5 · outbound

This paper cites Initial Results on Deep Learning for Joint Channel Equalization and Decoding,.

Joint Detection and Decoding: A Graph Neural Network Approach Initial Results on Deep Learning for Joint Channel Equalization and Decoding,

Reference 29

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raw_fallback, observed 2026-08-10T20:21:18.295521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cbed35fa-0f9d-4b99-8f61-6e5a8028fb8e · outbound

This paper cites Neural Network- Aided BCJR Algorithm for Joint Symbol Detection and Channel De- coding,.

Joint Detection and Decoding: A Graph Neural Network Approach Neural Network- Aided BCJR Algorithm for Joint Symbol Detection and Channel De- coding,

Reference 30

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raw_fallback, observed 2026-08-10T20:21:18.283578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 40b46544-0c4f-43ba-a4bd-a99f9651a21e · outbound

This paper cites Joint Equalization and LDPC Decoding,.

Joint Detection and Decoding: A Graph Neural Network Approach Joint Equalization and LDPC Decoding,

Reference 31

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raw_fallback, observed 2026-08-10T20:21:18.270013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f016b89d-3537-4c82-a65f-676f1b1e2f8b · outbound

This paper cites A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain,.

Joint Detection and Decoding: A Graph Neural Network Approach A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain,

Reference 32

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raw_fallback, observed 2026-08-10T20:21:18.254580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.497902Z digest=sha256:828555a7925bfab1916f1b7da254e23b2fad622bf66df4d56ab7d03b8dc125fc

Observation f1bb9b27-b754-4afc-b8db-b222d37fa567 · outbound

This paper cites Convergence behavior of iteratively decoded parallel concatenated codes,.

Joint Detection and Decoding: A Graph Neural Network Approach Convergence behavior of iteratively decoded parallel concatenated codes,

Reference 33

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raw_fallback, observed 2026-08-10T20:21:18.240364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.502113Z digest=sha256:dd16ce307f1fed96b4f16e63db277902667619cadbd26ece89d80350a9327b77

Observation 0a58aa6c-d9fa-481c-9203-6e9cc6d34142 · outbound

This paper cites Convergence analysis and optimal scheduling for multiple concatenated codes,.

Joint Detection and Decoding: A Graph Neural Network Approach Convergence analysis and optimal scheduling for multiple concatenated codes,

Reference 34

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raw_fallback, observed 2026-08-10T20:21:18.226934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.505842Z digest=sha256:18d65a15850e644ee5d0722de46e7c94d8083638afd821b7bfcc8bdb5d363d81

Observation 98cfe4df-ca20-4f9f-83bb-6fbfcf9e5b74 · outbound

This paper cites The turbo principle in mobile communications,.

Joint Detection and Decoding: A Graph Neural Network Approach The turbo principle in mobile communications,

Reference 35

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raw_fallback, observed 2026-08-10T20:21:18.214854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.509206Z digest=sha256:8077bf293b2120398e860531b2ca4547296b27797ba93592d8103a2c9c88b153

Observation 0c5d8b3b-4a1b-4359-b33c-db9dbab11790 · outbound

This paper cites A mathematical theory of communication,.

Joint Detection and Decoding: A Graph Neural Network Approach A mathematical theory of communication,

Reference 36

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no resolver link, observed 2026-08-10T20:21:17.512735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.512735Z digest=sha256:205c16584fe2c6ef501f3aaa288eb0154216b9de8e8d1f999f07b289eac4312e

Observation 3f55b412-856b-4aed-8e82-eea5601755de · outbound

This paper cites Extrinsic information transfer functions: model and erasure channel properties,.

Joint Detection and Decoding: A Graph Neural Network Approach Extrinsic information transfer functions: model and erasure channel properties,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.197371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.516102Z digest=sha256:07e97bdcbbf7b949abfa5b7ec3ecd63e4ed90909f1c4722e9d90d356af0e1769

Observation f0c7901b-c356-4024-aef7-e3baea782c92 · outbound

This paper cites Achievable Rates for Probabilistic Shaping.

Joint Detection and Decoding: A Graph Neural Network Approach Achievable Rates for Probabilistic Shaping

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T20:21:17.519969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.519969Z digest=sha256:bec2ade88ee19767452bceef1217567a6982d413fbf1192ac4dfb42673dab82b

Observation 9a890cff-8c70-4711-91dd-3d97ae13263b · outbound

This paper cites Trainable Communication Systems: Concepts and Prototype,.

Joint Detection and Decoding: A Graph Neural Network Approach Trainable Communication Systems: Concepts and Prototype,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.185365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.524307Z digest=sha256:3622b89437d21ad290f75ae7ef8e4aa75385f27953e14c2eb5f17008a7424fb2

Observation b309c3b6-5741-4de8-9fff-dfe897503372 · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks,.

Joint Detection and Decoding: A Graph Neural Network Approach Understanding the difficulty of training deep feedforward neural networks,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T20:21:17.528262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.528262Z digest=sha256:b4d86c302ad0abda53640c9a0519c7b09bb1909f1581b28d78b0c476af28f3a7

Observation 4671eb5b-14ab-4566-8661-25243f8f859c · outbound

This paper cites Graph Attention Networks.

Joint Detection and Decoding: A Graph Neural Network Approach Graph Attention Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T20:21:17.532899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.532899Z digest=sha256:95ac4fc5fcca00cb3718f7d20ce0b7e4375408257716f8d6d6d0b23162580925

Observation a2682560-9091-40f1-80bd-eb4651eb0f09 · outbound

This paper cites Adaptive channel memory truncation for maximum likelihood sequence estimation,.

Joint Detection and Decoding: A Graph Neural Network Approach Adaptive channel memory truncation for maximum likelihood sequence estimation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.156749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.537068Z digest=sha256:ce4dfe0bbecb09dbe8faf2f38efe27cedee5ead549e9d6c0401d3660a138c1db

Observation 5e470844-379f-453e-8dbf-3bd4b2dae2ee · outbound

This paper cites Optimal Channel Shortening for MIMO and ISI Channels,.

Joint Detection and Decoding: A Graph Neural Network Approach Optimal Channel Shortening for MIMO and ISI Channels,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.139492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.541992Z digest=sha256:deb9d123ac314e6fb785084ece4ec532588e8f2e7323b476b15a288088ffef31

Observation bb14c9dd-37e3-496d-afba-be68de566d4b · outbound

This paper cites On the application of factor graphs and the sum-product algorithm to isi channels,.

Joint Detection and Decoding: A Graph Neural Network Approach On the application of factor graphs and the sum-product algorithm to isi channels,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.127339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.546613Z digest=sha256:d911da0f7ae3b446ba888eef70f0d7fa374d9c2eb28fcc5857907bace44fa98e

Observation a1fc82c6-2ebe-4760-b431-58d131224d24 · outbound

This paper cites Block expectation propagation equalization for ISI channels,.

Joint Detection and Decoding: A Graph Neural Network Approach Block expectation propagation equalization for ISI channels,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.114424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.551408Z digest=sha256:419356f632ce79302c4e8aedde22bf282234e7cf0d13a52ed0a1868e5dfdac4f

Observation aed2e177-0d18-447a-94c9-2a155243898c · outbound

This paper cites Learned Belief- Propagation Decoding with Simple Scaling and SNR Adaptation,.

Joint Detection and Decoding: A Graph Neural Network Approach Learned Belief- Propagation Decoding with Simple Scaling and SNR Adaptation,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.101672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.556131Z digest=sha256:80a2da7dabfb402c78bcf0bfbe8151f6d631dfb4f9c5c6482c241dd83011774e

Observation 949fb9d1-5e60-4af9-bbac-847214ad17ba · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Joint Detection and Decoding: A Graph Neural Network Approach Adam: A Method for Stochastic Optimization

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T20:21:17.562799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.562799Z digest=sha256:ecba3984feb939dfa6325e65fa7a43019c63101007f74386eb3e345ec0dea495

Observation 98d9551c-2191-450d-a07c-ab680b38e76f · outbound

This paper cites Joint equalization and decoding: why choose the iterative solution?.

Joint Detection and Decoding: A Graph Neural Network Approach Joint equalization and decoding: why choose the iterative solution?

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.090282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.567238Z digest=sha256:561e5bc8502fc5f789c799c2d67594aa20009b64ef73dcf0e9b417069f940e67

Observation b81add4d-720e-4d09-9e7b-d1c7cdf2b483 · outbound

This paper cites Szczecinski and A.

Joint Detection and Decoding: A Graph Neural Network Approach Szczecinski and A

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.078038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.572693Z digest=sha256:e9e8e4e61e2a2265af81bc9f42aed8c18e5fa76c58601a6851621c7d4bee7cbe

Observation af51a38f-c6eb-4deb-89d6-679e5e43ca8b · outbound

This paper cites Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference,.

Joint Detection and Decoding: A Graph Neural Network Approach Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.066903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.579745Z digest=sha256:7ef9fba82f6b2a97f418d56d0e110cfd033cf74a643b85e33e5549b14ce3d6d7

Observation 060434d2-632c-4da6-a694-65f9e0efae91 · outbound

This paper cites Explainability in Graph Neural Networks: A Taxonomic Survey,.

Joint Detection and Decoding: A Graph Neural Network Approach Explainability in Graph Neural Networks: A Taxonomic Survey,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.054524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.584557Z digest=sha256:840d1f5bc216efea9be341fcb4934a2bf3158c26990813bcac1b24897f56f1b0

Observation 3ce2ba01-29b7-484f-86be-5567c8bda653 · outbound

This paper cites Local message passing on frustrated systems,.

Joint Detection and Decoding: A Graph Neural Network Approach Local message passing on frustrated systems,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.042640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.589919Z digest=sha256:cffd60bf6e598417560a52ebc1f41543b2da716e4e4d549a4a89309bc4690cff

Observation c6d54860-3aef-469b-bdf8-c65e8e345546 · outbound

This paper cites ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection,.

Joint Detection and Decoding: A Graph Neural Network Approach ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.031059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.593931Z digest=sha256:465ed1f275ff35a941e05e2553406d61104663abbdd8a6d8da7de49059edf971

Observation d605380b-ea98-47af-b289-c586afcffbfd · outbound

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

Joint Detection and Decoding: A Graph Neural Network Approach Sionna: An Open-Source Library for Next-Generation Physical Layer Research,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.014213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.597751Z digest=sha256:8ce1778a4078c0f10b823eb499c8a318891a47bc7340084fe8ee787e329ea026

Observation 8a7c3997-a8e4-49a1-9385-249ac75e2430 · outbound

This paper cites Bellman, Adaptive Control Processes: A Guided Tour.

Joint Detection and Decoding: A Graph Neural Network Approach Bellman, Adaptive Control Processes: A Guided Tour

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.998610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.601714Z digest=sha256:7850267ba5c1f493a8a57360d6ff23c3719ab1b033a3165a612e2f1510916458

Observation 91424927-0716-47b6-b613-60154e037599 · outbound

This paper cites High-Dimensional Data Analysis: The Curses and Bless- ings of Dimensionality,.

Joint Detection and Decoding: A Graph Neural Network Approach High-Dimensional Data Analysis: The Curses and Bless- ings of Dimensionality,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.985146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.605570Z digest=sha256:cbc0b47e88a45b34a479aefb58324a69dca43f5f3989a59e1f6f9497258b0b28

Observation 52df1734-a207-4e2f-bdba-d76014effead · outbound

This paper cites Bit-interleaved coded modula- tion,.

Joint Detection and Decoding: A Graph Neural Network Approach Bit-interleaved coded modula- tion,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.969277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.609518Z digest=sha256:717eca04e58fc98a710b9cbb0ad9218ad45b2553d62ee6ac1d13803cc31eba6c

Observation 1cdd6714-a042-4ee5-a6c7-e3375604d1ff · outbound

This paper cites Iterative correction of intersymbol interference: Turbo-equalization,.

Joint Detection and Decoding: A Graph Neural Network Approach Iterative correction of intersymbol interference: Turbo-equalization,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:18.307910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.613137Z digest=sha256:7f2fbf4841c36db278d15d5dc7613238df2437e5c62e1d4187c28da7cecf7f5a

Observation b0bd24b2-ba49-4620-81fb-f0f44d3fd81c · outbound

This paper cites DUIDD: Deep- Unfolded Interleaved Detection and Decoding for MIMO Wireless Systems,.

Joint Detection and Decoding: A Graph Neural Network Approach DUIDD: Deep- Unfolded Interleaved Detection and Decoding for MIMO Wireless Systems,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.951816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.616886Z digest=sha256:6c3b1a13315cce6dabcfe7f0e02be2f76507ec05f32f63d96c3c5f351bcd93de

Observation 99625a36-59fd-486f-8eb7-849a09009727 · outbound

This paper cites Neural Turbo Equalization: Deep Learning for Fiber-Optic Nonlinearity Compensation,.

Joint Detection and Decoding: A Graph Neural Network Approach Neural Turbo Equalization: Deep Learning for Fiber-Optic Nonlinearity Compensation,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.933228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.620756Z digest=sha256:bd8f1c12089848b79cf3b3dc8ca9146143ea2a09365c00b330206367c13c9a65

Observation 7e2c1876-f3ea-405f-aa9e-3f100a6dc4f7 · outbound

This paper cites Serial vs. Parallel Turbo-Autoencoders and Accelerated Training for Learned Channel Codes,.

Joint Detection and Decoding: A Graph Neural Network Approach Serial vs. Parallel Turbo-Autoencoders and Accelerated Training for Learned Channel Codes,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.917373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.624271Z digest=sha256:ea8d4d877ef11320e5bc0f28bdbc2d1ef8e62d60c209dd420ea28f49424c8157

Observation 4002caf7-b288-441b-9f98-29f5f2920301 · outbound

This paper cites Minimum mean squared error equalization using a priori information,.

Joint Detection and Decoding: A Graph Neural Network Approach Minimum mean squared error equalization using a priori information,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.900453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.628103Z digest=sha256:b42e8679b8b1490cc31c8131bcb750bdc3dfe3eb2c56711ef5990e958b76d60c

Observation c1e88861-9614-43dd-97f9-c8802550360b · outbound

This paper cites Turbo EP-Based Equalization: A Filter-Type Implementation,.

Joint Detection and Decoding: A Graph Neural Network Approach Turbo EP-Based Equalization: A Filter-Type Implementation,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.878925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.632089Z digest=sha256:35ecd23548c35f9b5e0f8c21bb4ffe21fd3348b79a7737439df889dfdce18b4e

Observation 433f6022-d1d9-462a-8d22-bef0d38a1c16 · outbound

This paper cites A fast algorithm for the inversion of general Toeplitz matrices,.

Joint Detection and Decoding: A Graph Neural Network Approach A fast algorithm for the inversion of general Toeplitz matrices,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.859467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.636424Z digest=sha256:af0b9e8a6e788776a9fb501ffc95b23cf23433dc9ca9447b103e4797e2cef51c

Observation 6b9026a3-7e15-4580-89ae-d088d5f6f177 · outbound

This paper cites Expectation Propagation as Turbo Equalizer in ISI Channels,.

Joint Detection and Decoding: A Graph Neural Network Approach Expectation Propagation as Turbo Equalizer in ISI Channels,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.843075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.640616Z digest=sha256:4ac962ac7d5b2cc1e5a62a7620fc593770876fc844406e8df5bcd65d231817f3

Observation 912942b3-f26e-48b9-9a77-aa8253a8e8b6 · outbound

This paper cites Learning Joint Detection, Equalization and Decoding for Short-Packet Communica- tions,.

Joint Detection and Decoding: A Graph Neural Network Approach Learning Joint Detection, Equalization and Decoding for Short-Packet Communica- tions,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.828893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.646379Z digest=sha256:96ed1c39d7b1c094b838c9908d640e4a115fd851ec30ad0bbcafe35536327d5f

Observation d00bf0bf-bbd8-417c-a782-3dbc59b23a58 · outbound

This paper cites Sparse Neural Network for Detection and Decoding of Non-Binary Polar-Coded SCMA,.

Joint Detection and Decoding: A Graph Neural Network Approach Sparse Neural Network for Detection and Decoding of Non-Binary Polar-Coded SCMA,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.816115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.653621Z digest=sha256:3be55e812554a7549fb9328fcf49c3d93f8e72dc18455d00a56120a9765acb2d

Observation 1f1ea19b-506c-4b89-80cf-b602a3826141 · outbound

This paper cites Design of a Standard-Compliant Real-Time Neural Receiver for 5G NR.

Joint Detection and Decoding: A Graph Neural Network Approach Design of a Standard-Compliant Real-Time Neural Receiver for 5G NR

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T20:21:17.658918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:21:17.658918Z digest=sha256:a6669ef1aa1942233a686cc429b263dd3058b05323180092f0e1c80df5e4329c

Observation 6b39bf9d-2ec8-4afd-b068-7de034995668 · outbound

This paper cites From Algorithm to Implementation: Enabling High-Throughput CNN- Based Equalization on FPGA for Optical Communications,.

Joint Detection and Decoding: A Graph Neural Network Approach From Algorithm to Implementation: Enabling High-Throughput CNN- Based Equalization on FPGA for Optical Communications,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.800950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.663464Z digest=sha256:ca0992abbde7f0089ecee3c403ecab4ab36133f6697afc4848b775b742718012

Observation 86ced5ef-66ad-4547-b952-366c5bfab12b · outbound

This paper cites Implementing neural network-based equalizers in a coherent optical transmission system using field-programmable gate arrays,.

Joint Detection and Decoding: A Graph Neural Network Approach Implementing neural network-based equalizers in a coherent optical transmission system using field-programmable gate arrays,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:21:17.786255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:21:17.667655Z digest=sha256:af08af4d5d95bcfcead1404a0616602d22f3126847265f9c255473d7244fc593

Pith citing papers

No inbound Pith citation observations are available.