Paper Citation Record · LEDGER

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications

As of 22 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2411.10101.

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

pith.paper-citation-record.v1
2411.10101 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:02:59.130636Z

measured 20 of 20 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:09:48.068770Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:09:50.453417Z

Reference resolution

19 of 19 outbound references displayed

verified exact11
verified fuzzy7
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee4a2149-10e6-40fb-99b8-603871e6930d · outbound

This paper cites Deep learning,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Deep learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T20:02:59.025855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 846b4b33-bdab-49ad-aa8f-c7c1fc002160 · outbound

This paper cites Roadmap on optical communications,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Roadmap on optical communications,

Reference 2

Resolution: verified exact; doi, observed 2026-08-12T20:02:59.177441Z

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 b1204219-dc83-4af5-a2cb-16bbaa43064d · outbound

This paper cites End-to-end Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications End-to-end Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.431738Z

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 3c24818d-38fa-4f3b-b046-6dc5d091be5b · outbound

This paper cites Neural networks-based equalizers for coherent optical transmission: Caveats and pitfalls,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Neural networks-based equalizers for coherent optical transmission: Caveats and pitfalls,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.557573Z

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 863fdf73-9803-4855-903f-854cab8940e3 · outbound

This paper cites Nonlinear equalization for optical communications based on entropy-regularized mean square error,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Nonlinear equalization for optical communications based on entropy-regularized mean square error,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.538400Z

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 c78cfe7d-01d5-4de8-b09d-b18db4f4a955 · outbound

This paper cites Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoders.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoders

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.406028Z

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 15fa08ca-c2ac-4ee1-ae64-079d12d5ec2b · outbound

This paper cites Unsupervised linear and nonlinear channel equalization and decoding using variational autoencoders,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Unsupervised linear and nonlinear channel equalization and decoding using variational autoencoders,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.517643Z

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 827c2bcc-1199-4983-a2eb-8918562168e6 · outbound

This paper cites Improving the Bootstrap of Blind Equalizers with Variational Autoencoders.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Improving the Bootstrap of Blind Equalizers with Variational Autoencoders

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.380328Z

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 8dc1a925-c505-459d-89b5-2a726536acac · outbound

This paper cites Blind channel equalization using vector-quantized variational autoencoders,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Blind channel equalization using vector-quantized variational autoencoders,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.500063Z

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 abbfc36a-6c0a-4cc9-ad2d-44e64bef90a8 · outbound

This paper cites Blind Frequency-Domain Equalization Using Vector-Quantized Variational Autoencoders.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Blind Frequency-Domain Equalization Using Vector-Quantized Variational Autoencoders

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.355862Z

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 1d41302c-b2c4-48ef-946a-9bbc2c208c74 · outbound

This paper cites CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.333385Z

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 c6cea740-8bf6-4483-bc69-73d23ba89600 · outbound

This paper cites Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.306991Z

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 b664b14c-2622-4da7-b728-e727e462aaf4 · outbound

This paper cites From algorithm to implementation: enabling high-throughput CNN-based equalization on FPGA for optical communications,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications From algorithm to implementation: enabling high-throughput CNN-based equalization on FPGA for optical communications,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.483686Z

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 ed861bb8-bb91-4134-beda-d8a79c5b0ce1 · outbound

This paper cites Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.282076Z

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 79ca1d3f-6ea8-4600-9990-0111ed542f0b · outbound

This paper cites Achieving High Throughput with a Trainable Neural-Network-Based Equalizer for Communications on FPGA.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Achieving High Throughput with a Trainable Neural-Network-Based Equalizer for Communications on FPGA

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.255611Z

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 7e9d5e88-75ee-43d1-a39f-a59d98b5150b · outbound

This paper cites Energy-efficient spiking neural network equalization for IM/DD systems with optimized neural encoding,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Energy-efficient spiking neural network equalization for IM/DD systems with optimized neural encoding,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.467029Z

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 b72b3f7d-4019-4cb4-80bf-9b6365d81484 · outbound

This paper cites Spiking neural network nonlinear demapping on neuromorphic hardware for IM/DD optical communication,.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Spiking neural network nonlinear demapping on neuromorphic hardware for IM/DD optical communication,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:02:59.449852Z

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 40837aad-d33b-4899-85de-af394dfa68a6 · outbound

This paper cites Spiking Neural Network Decision Feedback Equalization.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Spiking Neural Network Decision Feedback Equalization

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.230873Z

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 e04f9b77-af7a-4800-a666-9789b2947627 · outbound

This paper cites Efficient FPGA Implementation of an Optimized SNN-based DFE for Optical Communications.

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications Efficient FPGA Implementation of an Optimized SNN-based DFE for Optical Communications

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:02:59.203277Z

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 30c81e07-28b1-40c3-9aca-778714db0f18 · inbound

Integrated recurrent optical spectral slicer for equalization of 100-km C-band IM/DD transmission cites this paper.

Integrated recurrent optical spectral slicer for equalization of 100-km C-band IM/DD transmission Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:09:50.542288Z

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.