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Paper Citation Record · LEDGER

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback

As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.06833.

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

pith.paper-citation-record.v1
2507.06833 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:59:19.037706Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

16 of 16 outbound references displayed

  • verified exact2
  • verified fuzzy11
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e995002-c205-41f1-a94f-a88ba1076f8e · outbound

This paper cites Massive MIMO evolution toward 3GPP release 18,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Massive MIMO evolution toward 3GPP release 18,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:25.040568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:16.279790Z digest=sha256:761dd710d11e0fd51ab58855139d7460d7ef01b1f8415978fc64a258d64d8a2d

Observation fe944ba8-54a2-4a4d-88bc-f450152bce72 · outbound

This paper cites an unresolved cited work.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:59:24.580460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:16.410480Z digest=sha256:cf75bed87c078a7ae48d3e5915c528b09fc651ba6584aad512faefb7f4598039

Observation 3957ead0-675e-4f7b-aef0-539f6c67ad2b · outbound

This paper cites TypeII-CsiNet: CSI feedback with TypeII codebook,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback TypeII-CsiNet: CSI feedback with TypeII codebook,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:24.198553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:16.564791Z digest=sha256:41db2909a5fd5f7e157cc6acbcd94e944d3cdd5f6c08d16ac9644ffd17fff227

Observation b86c4e83-7728-445c-8bb6-d78348d99161 · outbound

This paper cites Deep learning for massive MIMO CSI feedback,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Deep learning for massive MIMO CSI feedback,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:23.766447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:16.728858Z digest=sha256:7dc62485b2c7162bbbd8d8ace9e4f06b72957dcc05e9bbfe3b37ae58a03bc87e

Observation e2e1b5f1-a00b-44cd-96b8-5b6c854575f5 · outbound

This paper cites Convolutional neural network-based multiple-rate compressive sensing for massive MIMO CSI feedback: Design, simulation, and analysis,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Convolutional neural network-based multiple-rate compressive sensing for massive MIMO CSI feedback: Design, simulation, and analysis,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:23.307926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:16.953417Z digest=sha256:524b6c69a32cf4d02858ae67317a983611fa80b42e42aebe62bf00e3ae31c0e1

Observation c8834295-357e-4cde-b8b2-864d50b68afa · outbound

This paper cites TransNet: Full attention network for CSI feedback in FDD massive MIMO system,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback TransNet: Full attention network for CSI feedback in FDD massive MIMO system,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:22.953987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:17.120983Z digest=sha256:3853cb3272969929cc144752ce0ec26bac9e26f38b88b4dee8764499a643692e

Observation ff94d6f7-4540-48c9-ae20-34cf1e7fc87c · outbound

This paper cites Overview of deep learning- based CSI feedback in massive MIMO systems,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Overview of deep learning- based CSI feedback in massive MIMO systems,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:22.468564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:17.329559Z digest=sha256:f67336f72c6d92e9c6341e36a0e1c1672b6b0f8b4ad08e4099df1ac1a2cde9d5

Observation 0339ce50-1771-4f8b-aa3e-7bf31273c107 · outbound

This paper cites an unresolved cited work.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:59:22.086449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:17.485064Z digest=sha256:e6f378799322c7730e3d986a30e2b39c2f9a2b061f230c6c9fbb97b93974bfb4

Observation ff2a8c3c-4933-4c96-88a2-b4951fc792f4 · outbound

This paper cites Multi-domain correlation- aided implicit CSI feedback using deep learning,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Multi-domain correlation- aided implicit CSI feedback using deep learning,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:21.809760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:17.700288Z digest=sha256:e87f73ab93d334862451c268eaf32f8b90cee9a74b16d43c2a032eff8fbcdb24

Observation ae7a5361-85cc-4fc7-980a-31edcc77f1c3 · outbound

This paper cites Generalizing Deep Learning-Based CSI Feedback in Massive MIMO via ID-Photo-Inspired Preprocessing.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Generalizing Deep Learning-Based CSI Feedback in Massive MIMO via ID-Photo-Inspired Preprocessing

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:59:19.801704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:17.924281Z digest=sha256:bae477f546adb06184854823ba20225168d313bf3d7bae4fcf13ca21b8bb993e

Observation eb5cdf09-34e1-4b4a-90b4-24c291ff0c36 · outbound

This paper cites Path evolution model for endogenous channel digital twin towards 6G wireless networks,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Path evolution model for endogenous channel digital twin towards 6G wireless networks,

Reference 11

Resolution
verified exact
raw_fallback, observed 2026-08-06T18:59:19.413159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:18.096099Z digest=sha256:d3b91b6f6c2020ebe1a4030fabfa380692c20871b852e400af75fbdff9b9f286

Observation 0cfce8fd-1e9b-465f-889a-ddcfdb990df6 · outbound

This paper cites Quantization adaptor for bit- level deep learning-based massive MIMO CSI feedback,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Quantization adaptor for bit- level deep learning-based massive MIMO CSI feedback,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:21.496914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:18.277588Z digest=sha256:d9f7ef9f4006047896921c60054d2e480352b7cdd53d53f4e2e0437e94f1b692

Observation 5294862a-c09f-4752-b39d-c498ce81617c · outbound

This paper cites Modeling the data-generating process is necessary for out-of-distribution generalization,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Modeling the data-generating process is necessary for out-of-distribution generalization,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:21.099580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:18.425144Z digest=sha256:10b99eb9104e71dd62c54fecfa5b7a8643154bf9d1e254e9514fac51b78b5cc0

Observation 3a9b6968-8b18-4a4c-8681-2d41861d44ca · outbound

This paper cites Beamspace channel estimation for wideband millimeter-wave MIMO: A model- driven unsupervised learning approach,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Beamspace channel estimation for wideband millimeter-wave MIMO: A model- driven unsupervised learning approach,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:20.692617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:18.569576Z digest=sha256:30e3779a80c38221eb19bc73e3881c6ecf34c94888c82fe6b6989fef602750d1

Observation 04a594a3-a5f4-40f1-9bf3-414ee0ebb176 · outbound

This paper cites Deep learning assisted calibrated beam training for millimeter-wave communication systems,.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback Deep learning assisted calibrated beam training for millimeter-wave communication systems,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:59:20.157071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:59:18.808458Z digest=sha256:e890eaaa575a87e00a6c7e7fe3986176feeaf4a9333d65899034f19bff83dc43

Observation f4705c83-52be-4f20-926c-481767151f37 · outbound

This paper cites WAIR-D: Wireless AI Research Dataset.

Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback WAIR-D: Wireless AI Research Dataset

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:59:19.037706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.