Paper Citation Record · LEDGER

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.05407.

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

pith.paper-citation-record.v1
2506.05407 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:57:17.001081Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

18 of 18 outbound references displayed

verified exact1
verified fuzzy9
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 717e9ab4-9515-4a24-a950-05bd8d040c79 · outbound

This paper cites Accessed: 2025- 01-22.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Accessed: 2025- 01-22

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.286244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e27ea6bb-e0e3-46bf-b945-b771477782b7 · outbound

This paper cites J., and Choi, J.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs J., and Choi, J

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:16.973698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17cdabc4-1986-49b6-a69a-fa2d73ac876f · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:16.975782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84c53f06-a6f4-4254-8cab-564dfa26d640 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:16.979891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27b76354-9f82-4a7e-934f-751d566b753e · outbound

This paper cites Progen: Progressive zero-shot dataset generation via in-context feedback.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Progen: Progressive zero-shot dataset generation via in-context feedback

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.273807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 16d843a8-6165-41b2-9611-638d2dbd49ed · outbound

This paper cites Experimental Details We have included the necessary experimental details in the main body, and show more details here.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Experimental Details We have included the necessary experimental details in the main body, and show more details here

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.267295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ab260e4a-43be-477c-b132-12b75c884c22 · outbound

This paper cites Following PE (Lin et al., 2024), we manually implement SD on a server, providing an SD API with both text-to-image (t2i) and image-to-image (i2i) features.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Following PE (Lin et al., 2024), we manually implement SD on a server, providing an SD API with both text-to-image (t2i) and image-to-image (i2i) features

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.261022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 764a8a05-8b96-4f82-9811-ecca32b0eafb · outbound

This paper cites A DOMAIN image with LABEL.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs A DOMAIN image with LABEL

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.253655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7abe554a-b157-4101-af8f-3873675a2e3a · outbound

This paper cites refine this description of images to introduce rich context:.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs refine this description of images to introduce rich context:

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.246810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d19d91e5-db7a-4dcc-a33a-adf3423709b0 · outbound

This paper cites We compute theσfor GM based on Theorem 3.2 given a total privacy costϵ ∗.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs We compute theσfor GM based on Theorem 3.2 given a total privacy costϵ ∗

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.239907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 90c09bd6-fce7-41b8-b0d2-1d6c2bbe599f · outbound

This paper cites To balance the privacy-utility trade-off, selecting an appropriateϵ ∗ is crucial for different tasks and environments (Lin et al., 2024).

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs To balance the privacy-utility trade-off, selecting an appropriateϵ ∗ is crucial for different tasks and environments (Lin et al., 2024)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.233090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 989df8c2-1c3e-49e8-bead-a801ffaf3c10 · outbound

This paper cites an unresolved cited work.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:57:17.225944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3e84486d-8f5c-4b05-aafe-1850c32e42f1 · outbound

This paper cites an unresolved cited work.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:57:17.218760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 340975a2-b54b-40cc-9106-619652dd5d11 · outbound

This paper cites an unresolved cited work.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:57:17.280383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 509074e2-e1a8-4421-80f5-4ad3b1c63463 · outbound

This paper cites H., Chen, Z., and Cao, Y.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs H., Chen, Z., and Cao, Y

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:16.964327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc442f46-86ff-4e75-9560-81e4335a20b2 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs A Simple Framework for Contrastive Learning of Visual Representations

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:17.292181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7d086eed-02ff-4b41-bf02-029684f548c7 · outbound

This paper cites Differentially Private Diffusion Models Generate Useful Synthetic Images.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:16.966605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fde4b196-b2f6-48ba-b179-6d43c30c01bc · outbound

This paper cites Differentially Private Federated Learning for Resource-Constrained Internet of Things.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs Differentially Private Federated Learning for Resource-Constrained Internet of Things

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:57:17.140401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.