Paper Citation Record · LEDGER

Split-and-Denoise: Protect large language model inference with local differential privacy

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2310.09130.

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

pith.paper-citation-record.v1
2310.09130 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:35:58.200046Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:18:03.500027Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9f6a681b-f941-4bc8-a7c3-c16c45bf3b54 · inbound

Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions cites this paper.

Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T18:31:12.623235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a29e6527-9af8-41d7-b38d-4b4e63ba7b83 · inbound

Preserving Privacy and Utility in LLM-Based Product Recommendations cites this paper.

Preserving Privacy and Utility in LLM-Based Product Recommendations Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T04:35:58.200046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b739dcd-b212-4153-8558-76266306ca6e · inbound

BeamClean: Language Aware Embedding Reconstruction cites this paper.

BeamClean: Language Aware Embedding Reconstruction Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:06.128863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91a4826b-4825-4a25-9e91-0a3f1e009e72 · inbound

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance cites this paper.

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:01.136683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a626438-b103-4e2e-8440-fe231846db3f · inbound

Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform cites this paper.

Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:48.796083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57a81a57-b442-43f1-8466-977753cf6078 · inbound

SoK: Semantic Privacy in Large Language Models cites this paper.

SoK: Semantic Privacy in Large Language Models Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T21:40:33.135936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0625d614-5525-4f6a-af1d-41e1aa009833 · inbound

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 134

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:14.922469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9258edc9-78d4-45ef-937a-484410f7e0ef · inbound

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage cites this paper.

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T16:50:24.622227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8f81c82-f12b-4b05-a672-acca39ce207c · inbound

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization cites this paper.

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T16:10:53.322326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e3d4642-4515-415b-8db0-39fa8bc1ae84 · inbound

Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning cites this paper.

Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:30:31.744331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8bbfc7fc-105d-4417-81af-0d17e1c2f3ea · inbound

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation cites this paper.

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:41:53.851760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dc7c062a-3ff7-4b6f-818d-bd26cf41b0e2 · inbound

PAAC: Privacy-Aware Agentic Device-Cloud Collaboration cites this paper.

PAAC: Privacy-Aware Agentic Device-Cloud Collaboration Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:31:23.855844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8c83185d-78b6-42e3-addd-f452cfaed01a · inbound

Defense Against Prompt Inversion Attacks: An Information-Theoretic Approach for LLM Collaborative Inference cites this paper.

Defense Against Prompt Inversion Attacks: An Information-Theoretic Approach for LLM Collaborative Inference Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 154

Resolution: verified exact; arxiv_id, observed 2026-07-03T11:18:03.501440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c36f73c1-69bf-41a8-95ca-810241f11245 · inbound

Efficient and Privacy Aware Edge Cloud Collaborative Inference for Large Language Models cites this paper.

Efficient and Privacy Aware Edge Cloud Collaborative Inference for Large Language Models Split-and-Denoise: Protect large language model inference with local differential privacy

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T06:42:17.678536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.