Paper Citation Record · LEDGER

Learning to Gridize: Segment Physical World by Wireless Communication Channel

As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.15386.

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

pith.paper-citation-record.v1
2507.15386 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:40:02.874391Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

36 of 36 outbound references displayed

verified exact1
verified fuzzy25
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6f4750ce-b05c-4211-b497-7650d8f25f17 · outbound

This paper cites SRCON: A data-driven network performance simulator for real-world wireless networks,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel SRCON: A data-driven network performance simulator for real-world wireless networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.992575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d15049d-917b-4661-899e-cfbf19af78aa · outbound

This paper cites A survey of recent advances in optimization methods for wireless communications,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel A survey of recent advances in optimization methods for wireless communications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.976505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4db860d9-2723-4791-8955-a2efbd19ff70 · outbound

This paper cites Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks

Reference 3

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Source-reported events for the cited work

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Observation 820763eb-d4fb-4eee-b54d-cd6f1c21bcf9 · outbound

This paper cites Multi-grid-based localized statistical channel modeling: A radio map approach,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Multi-grid-based localized statistical channel modeling: A radio map approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.959778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3b836bd1-4704-4c00-8064-13fb0cadbada · outbound

This paper cites A physics-based and data-driven approach for localized statistical channel modeling,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel A physics-based and data-driven approach for localized statistical channel modeling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.940260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7957056a-d405-4b04-a262-faa0955f4691 · outbound

This paper cites FedLoc: Federated learning framework for data-driven cooperative localization and location data processing,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel FedLoc: Federated learning framework for data-driven cooperative localization and location data processing,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.923003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1335ae88-b2de-4df2-b40f-808d314708f4 · outbound

This paper cites NR; Requirements for Support of Radio Resource Manage- ment,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel NR; Requirements for Support of Radio Resource Manage- ment,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.906412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d2cd55eb-9abd-459e-8eb0-2897d0436d1d · outbound

This paper cites Spatial partitioning method, apparatus, device, medium, and program product,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Spatial partitioning method, apparatus, device, medium, and program product,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.887047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 401e2bac-14e8-4c5e-ba16-03bdac589f97 · outbound

This paper cites Neural discrete representation learning,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Neural discrete representation learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.869288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43fae8cc-2d45-4728-8666-b3dd62841274 · outbound

This paper cites Zero-shot text-to-image generation,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Zero-shot text-to-image generation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.848480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e02304ba-a57f-4567-bca9-dd6331b7986e · outbound

This paper cites Jukebox: A Generative Model for Music.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Jukebox: A Generative Model for Music

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:59.972913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6068ab3-5b25-45c0-b42f-1985466b6718 · outbound

This paper cites Tokenflow: Unified image tokenizer for multi- modal understanding and generation,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Tokenflow: Unified image tokenizer for multi- modal understanding and generation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.831289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bee98988-8ffd-4508-9829-caef537bc4d1 · outbound

This paper cites VQ-V AE empowered wireless commu- nication for joint source-channel coding and beyond,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel VQ-V AE empowered wireless commu- nication for joint source-channel coding and beyond,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.808996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 34670f1f-a38c-4636-8119-f4847a8e5724 · outbound

This paper cites Cox, An Introduction to 5G: The New Radio, 5G Network and Beyond.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Cox, An Introduction to 5G: The New Radio, 5G Network and Beyond

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.788931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5da7df29-5622-4f99-82f3-8ea8b26c8b51 · outbound

This paper cites Tse and P.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Tse and P

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.766830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c7ab2c09-7c79-4548-a383-49b45aaea07f · outbound

This paper cites Study on Channel Model for Frequencies from 0.5 to 100 GHz,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Study on Channel Model for Frequencies from 0.5 to 100 GHz,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.746155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6fc40651-e50f-49e4-880e-64bf830dd16e · outbound

This paper cites an unresolved cited work.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:40:04.722864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 00785b1b-3b48-4440-b1e7-43e444451743 · outbound

This paper cites Inexact block coordinate descent algorithms for nonsmooth nonconvex optimization,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Inexact block coordinate descent algorithms for nonsmooth nonconvex optimization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.699119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4d409996-789f-446a-b97c-3b298d4d1b34 · outbound

This paper cites Proximal algorithms,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Proximal algorithms,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.680325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6c9afe6c-0ae9-4fa6-bd30-7965e06a2116 · outbound

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Learning to Gridize: Segment Physical World by Wireless Communication Channel Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:40:04.657118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a5877d31-8699-468d-9045-04f41934c85d · outbound

This paper cites Tutorial on amortized optimization,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Tutorial on amortized optimization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.632297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 68c87c92-2d35-45cf-803e-84592aee1a0a · outbound

This paper cites Visualizing data using t-sne,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Visualizing data using t-sne,

Reference 22

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Source-reported events for the cited work

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Observation 683984aa-6ca1-43fb-bda2-d64388585ef1 · outbound

This paper cites Fast decoding in sequence models using discrete latent variables,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Fast decoding in sequence models using discrete latent variables,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.592575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0a6f2dc6-b098-4141-9bd1-c81e4a5cacab · outbound

This paper cites Theory and Experiments on Vector Quantized Autoencoders.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Theory and Experiments on Vector Quantized Autoencoders

Reference 24

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Source-reported events for the cited work

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Observation c19b6411-985f-4c86-8cd7-ce78945edf8c · outbound

This paper cites Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.573756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f726fa8b-ee11-4fc2-b42d-3ef5ab5282bd · outbound

This paper cites Least squares quantization in PCM,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Least squares quantization in PCM,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:01.597572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 740f6324-2518-4447-82b7-6ccc56a5e208 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Adam: A Method for Stochastic Optimization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:01.679745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 715a2511-ff5f-499c-a0c4-847f9851fe38 · outbound

This paper cites torch.tensor.detach.

Learning to Gridize: Segment Physical World by Wireless Communication Channel torch.tensor.detach

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.451702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 05fd6fd5-7ed4-451f-8c5d-d06fe4d3c25e · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Decoupled Weight Decay Regularization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:01.984377Z

Source-reported events for the cited work

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Observation 55d51990-82e5-4838-889b-aea519e4055d · outbound

This paper cites Discrete latent variables,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Discrete latent variables,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.259005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2aec2c30-bcac-47b0-a260-1445f36f7ad9 · outbound

This paper cites Attention is all you need,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Attention is all you need,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:04.002069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 75537e83-cf8e-48f9-94a4-1786b9f80b3d · outbound

This paper cites Inductive representation learning on large graphs,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Inductive representation learning on large graphs,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:03.738290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6e8c4b57-4e4f-4a7d-9e26-e9bf1ee5de71 · outbound

This paper cites Attentional Graph Neural Network Is All You Need for Robust Massive Network Localization.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Attentional Graph Neural Network Is All You Need for Robust Massive Network Localization

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:40:03.133308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fde5d4c0-993a-40b6-9d24-d71b802c5353 · outbound

This paper cites Comparing partitions,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Comparing partitions,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:02.594234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 107169e3-f8a5-4eda-92f5-12965a870879 · outbound

This paper cites Cluster ensembles—a knowledge reuse frame- work for combining multiple partitions,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel Cluster ensembles—a knowledge reuse frame- work for combining multiple partitions,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:03.499790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d41aeadb-606f-453c-a751-5d7537b5eb01 · outbound

This paper cites V-measure: A conditional entropy- based external cluster evaluation measure,.

Learning to Gridize: Segment Physical World by Wireless Communication Channel V-measure: A conditional entropy- based external cluster evaluation measure,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:03.393357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.