Paper Citation Record · LEDGER

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy

As of 18 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2501.03451.

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

pith.paper-citation-record.v1
2501.03451 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:58:47.206610Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:26:20.938452Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

61 of 61 outbound references displayed

verified exact0
verified fuzzy50
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

Observation f322e4f3-66f1-49d4-a35f-95ab0853bfb5 · outbound

This paper cites Deep learning with differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Deep learning with differential privacy,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.180387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d7b4bb1-93a5-45a3-a3b0-4094e72a05e3 · outbound

This paper cites Secure deep graph generation with link differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Secure deep graph generation with link differential privacy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.163713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 48ced686-1c32-4d4d-813d-03d748baf39e · outbound

This paper cites Releasing Graph Neural Networks with Differential Privacy Guarantees.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Releasing Graph Neural Networks with Differential Privacy Guarantees

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:46.976613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f581742c-dd49-4000-ab66-b7473a9e0cab · outbound

This paper cites Node-Level Differentially Private Graph Neural Networks.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Node-Level Differentially Private Graph Neural Networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:46.981238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bb263e7-48b3-454e-831c-e3c5cca414f8 · outbound

This paper cites DPAR: Decoupled graph neural networks with node-level differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy DPAR: Decoupled graph neural networks with node-level differential privacy,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.147986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 991ca1b2-eac8-4248-a35c-f91ab5296e04 · outbound

This paper cites GAP: Differentially private graph neural networks with aggregation perturbation,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy GAP: Differentially private graph neural networks with aggregation perturbation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.133638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a65b30e5-9038-44e7-ac6b-dbd63abde14b · outbound

This paper cites ProGAP: Progressive graph neu- ral networks with differential privacy guarantees,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy ProGAP: Progressive graph neu- ral networks with differential privacy guarantees,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.118420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7723b9a7-d505-4eb0-895b-5e8afaf9719a · outbound

This paper cites Preserving node-level privacy in graph neural networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Preserving node-level privacy in graph neural networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.103741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation de12d44b-e838-4d50-9c52-ba7886620441 · outbound

This paper cites DeepWalk: Online learning of social representations,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy DeepWalk: Online learning of social representations,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.090028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93432558-14f8-458c-929a-484d475b277c · outbound

This paper cites LINE: Large-scale information network embedding,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy LINE: Large-scale information network embedding,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.058394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 718e8b2e-2a08-4fee-865a-0c2ae87c3eb4 · outbound

This paper cites PTE: Predictive text embedding through large-scale heterogeneous text networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy PTE: Predictive text embedding through large-scale heterogeneous text networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.044573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6f28bd69-ecfe-4090-9d6f-6245fcf56a40 · outbound

This paper cites node2vec: Scalable feature learning for networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy node2vec: Scalable feature learning for networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.030205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f35d8913-e573-4d48-856e-cd384edd506b · outbound

This paper cites Dynamic network embedding: An extended approach for skip-gram based network em- bedding,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Dynamic network embedding: An extended approach for skip-gram based network em- bedding,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:48.011822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c588aa5e-e642-4fb5-bd3d-19d1c9b35c82 · outbound

This paper cites Calibrating noise to sensitivity in private data analysis,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Calibrating noise to sensitivity in private data analysis,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.991278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 828d111b-1b4c-4833-b978-483bb55fb290 · outbound

This paper cites Accurate estimation of the degree distribution of private networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Accurate estimation of the degree distribution of private networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.978302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7a8846f8-9b39-4b09-a8f9-36e804cb4f13 · outbound

This paper cites Differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differential privacy,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.966149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b8afcc1-1eda-42bc-a86c-cc530ec44b76 · outbound

This paper cites R ´enyi differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy R ´enyi differential privacy,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.954337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76a693ba-229c-48e4-a75f-96f0e744c81b · outbound

This paper cites Emergence of scaling in random net- works,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Emergence of scaling in random net- works,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.039956Z

Source-reported events for the cited work

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Observation 57aba991-ec73-453b-ba2c-7a45c7dbad9a · outbound

This paper cites Predicting missing links via local information,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Predicting missing links via local information,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.043957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8938e9f8-f7e5-4390-88d4-9a44ab125d39 · outbound

This paper cites A new status index derived from sociometric analysis,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy A new status index derived from sociometric analysis,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.047772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d740a34b-576a-4b62-9e2f-67fb52d52b10 · outbound

This paper cites Topic-sensitive pagerank,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Topic-sensitive pagerank,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.920410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5ad45082-dbad-4553-9505-e5253f54c26e · outbound

This paper cites Network repre- sentation learning with rich text information,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Network repre- sentation learning with rich text information,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.907090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13bbac3b-386c-46f4-816d-b528a8b56b0a · outbound

This paper cites Model inversion attacks against collaborative inference,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Model inversion attacks against collaborative inference,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.894482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 38a82a04-8d51-4f60-97bd-755f12454686 · outbound

This paper cites Network embedding as matrix factorization: Unifying DeepWalk, LINE, PTE, and node2vec,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Network embedding as matrix factorization: Unifying DeepWalk, LINE, PTE, and node2vec,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.882158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b0c482a7-c675-4b90-89e8-ec6330dcb206 · outbound

This paper cites Subsampled r ´enyi differential privacy and analytical moments accountant,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Subsampled r ´enyi differential privacy and analytical moments accountant,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.870214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 12662f01-b759-41a6-bf14-640782ccdf64 · outbound

This paper cites Poission subsampled r´enyi differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Poission subsampled r´enyi differential privacy,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.858465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 020740e0-9b50-4e36-859e-c436a623eb65 · outbound

This paper cites R\'enyi Differential Privacy of the Sampled Gaussian Mechanism.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy R\'enyi Differential Privacy of the Sampled Gaussian Mechanism

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.072915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc257285-0a16-44f2-a463-1ff59e9c9191 · outbound

This paper cites Differentially private opti- mization on large model at small cost,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially private opti- mization on large model at small cost,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.847952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68dbdd67-f645-47ac-ba2c-6b737373b924 · outbound

This paper cites Toward understanding and evaluating structural node embeddings,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Toward understanding and evaluating structural node embeddings,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.835403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7736c840-a8d7-43ce-8109-8538ce3f5f32 · outbound

This paper cites BioGRID: A general repository for interaction datasets,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy BioGRID: A general repository for interaction datasets,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.824206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b2407964-0d7a-4a31-ab6b-87b42f81491f · outbound

This paper cites Link prediction based on graph neural networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Link prediction based on graph neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.811454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ae3bf576-3b19-4f5d-be48-edaf7526a419 · outbound

This paper cites Understanding and improvement of adversarial training for network embedding from an optimization perspective,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Understanding and improvement of adversarial training for network embedding from an optimization perspective,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.797322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1ae52ef8-3eb4-4913-9a69-ea96110f4e36 · outbound

This paper cites PRUNE: Preserving proximity and global ranking for network embedding,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy PRUNE: Preserving proximity and global ranking for network embedding,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.784008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 79e4e000-78b4-4486-931f-ecde8a6e8673 · outbound

This paper cites A unified framework for community detection and network representation learning,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy A unified framework for community detection and network representation learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.770559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68c79315-507b-4da0-9d9d-15b18164f1a7 · outbound

This paper cites k-anonymity: A model for protecting privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy k-anonymity: A model for protecting privacy,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.757458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bbb3aa44-3d3c-4c04-a00e-9d98e0a5ef60 · outbound

This paper cites l-diversity: Privacy beyondk-anonymity,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy l-diversity: Privacy beyondk-anonymity,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.744495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4541e4b5-8ddd-4c2b-905e-a57296b14daa · outbound

This paper cites Private search on key-value stores with hierarchical indexes,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Private search on key-value stores with hierarchical indexes,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.729781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb14a931-cba4-441f-b23c-207f65d943aa · outbound

This paper cites Differentially private empirical risk minimization,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially private empirical risk minimization,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.715197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41c9a5ba-99aa-450e-a125-1fec46b38748 · outbound

This paper cites Private empirical risk mini- mization: Efficient algorithms and tight error bounds,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Private empirical risk mini- mization: Efficient algorithms and tight error bounds,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.701853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f735d58-41c1-42e0-bf9b-79a96003c3f1 · outbound

This paper cites CALM: Consistent adaptive local marginal for marginal release under local differential pri- vacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy CALM: Consistent adaptive local marginal for marginal release under local differential pri- vacy,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.687977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 65a0aa0e-0065-4f15-a7cf-8a7604353980 · outbound

This paper cites Beyond Value Perturbation: Local differential privacy in the temporal setting,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Beyond Value Perturbation: Local differential privacy in the temporal setting,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.673806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e18f7846-c91b-4ff1-accc-a72c7c80834c · outbound

This paper cites PrivSyn: Differentially private data synthesis,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy PrivSyn: Differentially private data synthesis,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.660064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2bf25ffb-34f8-473b-844c-477052c08069 · outbound

This paper cites Stateful Switch: Optimized time series release with local differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Stateful Switch: Optimized time series release with local differential privacy,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.646137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 30ae8d20-7b0a-48bc-897a-12a9049b8c95 · outbound

This paper cites Trajectory data collection with local differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Trajectory data collection with local differential privacy,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.631505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e873e818-0311-40da-b069-30042480c873 · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Learning Differentially Private Recurrent Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.141226Z

Source-reported events for the cited work

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Observation 1fa82927-d033-43c3-9c28-1644b9798419 · outbound

This paper cites Stochastic gradient descent with differentially private updates,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Stochastic gradient descent with differentially private updates,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.614952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a7a11935-a1d7-43c6-ae2e-fd64bc3bd10d · outbound

This paper cites Boosting and differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Boosting and differential privacy,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.599681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0078622-6f90-4869-b8c6-528a7f7b2f62 · outbound

This paper cites Stochastic adaptive line search for differentially private optimization,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Stochastic adaptive line search for differentially private optimization,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.586472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1037680e-d577-47ec-9609-3464cc731502 · outbound

This paper cites Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.157127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9be2dd-94b8-4196-9760-1272af009136 · outbound

This paper cites Tem- pered sigmoid activations for deep learning with differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Tem- pered sigmoid activations for deep learning with differential privacy,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.572393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 96975b6a-afab-4a79-98e3-7aa552df70bc · outbound

This paper cites Differentially Private Learning Needs Better Features (or Much More Data).

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially Private Learning Needs Better Features (or Much More Data)

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.165539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cb3fb6f-87c0-4fb6-9001-ecc0d99c604e · outbound

This paper cites AdaCliP: Adaptive Clipping for Private SGD.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy AdaCliP: Adaptive Clipping for Private SGD

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.169984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7961c317-b3c9-4c78-bb1e-baa0daee953f · outbound

This paper cites Differentially-private deep learning from an optimization perspective,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially-private deep learning from an optimization perspective,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.558070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe16152f-aa8d-43dc-b207-55a168220f07 · outbound

This paper cites Differentially private model publishing for deep learning,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially private model publishing for deep learning,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.543692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 47020fcd-d161-4231-9b6e-198bf71c0c03 · outbound

This paper cites DPSUR: Accelerating differentially private stochastic gradient descent using selective update and release,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy DPSUR: Accelerating differentially private stochastic gradient descent using selective update and release,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.528125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 67f01072-32f4-4684-89de-9e4e9fa950a7 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Efficient Estimation of Word Representations in Vector Space

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:47.186208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b64d184b-17aa-4780-aa8e-459204cd1dec · outbound

This paper cites Distributed representations of words and phrases and their composi- tionality,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Distributed representations of words and phrases and their composi- tionality,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.513370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5d29d0b2-e04b-4898-b2c9-ffa970226c62 · outbound

This paper cites Differentially-private next- location prediction with neural networks,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially-private next- location prediction with neural networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.493892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe4ba573-4e66-40d4-8962-f4be99b314ae · outbound

This paper cites Differentially private fed- erated knowledge graphs embedding,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Differentially private fed- erated knowledge graphs embedding,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.479305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5aa8626e-d800-49be-a213-9942756e6020 · outbound

This paper cites A framework for differentially-private knowledge graph embeddings,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy A framework for differentially-private knowledge graph embeddings,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.465947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bc8b70dc-00f7-4b09-9bb8-98d94f31e86b · outbound

This paper cites FedWalk: Communication efficient federated unsu- pervised node embedding with differential privacy,.

Structure-Preference Enabled Graph Embedding Generation under Differential Privacy FedWalk: Communication efficient federated unsu- pervised node embedding with differential privacy,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:58:47.450458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 40f61ae3-65f6-45d4-a6e6-825b589bfe89 · inbound

Evaluating Loss Functions for Graph Neural Networks: Towards Pretraining and Generalization cites this paper.

Evaluating Loss Functions for Graph Neural Networks: Towards Pretraining and Generalization Structure-Preference Enabled Graph Embedding Generation under Differential Privacy

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T00:26:20.933649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b34df0ed-f01a-4782-92ef-8c3c108d98fe · inbound

Evaluating Loss Functions for Graph Neural Networks: Towards Pretraining and Generalization cites this paper.

Evaluating Loss Functions for Graph Neural Networks: Towards Pretraining and Generalization Structure-Preference Enabled Graph Embedding Generation under Differential Privacy

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:26:21.016694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.