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Paper Citation Record · LEDGER

Styleclone: Face Stylization with Diffusion Based Data Augmentation

As of 17 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2508.17045.

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

pith.paper-citation-record.v1
2508.17045 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:12:50.101864Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation deb9d96d-aa86-4969-8ce0-a522e6ffdbdd · outbound

This paper cites Values show percentage of failed generations evaluated by � � � and � � � in each evaluation cycle.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Values show percentage of failed generations evaluated by � � � and � � � in each evaluation cycle

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:12:50.330828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.068231Z digest=sha256:82e35e79435dd1610f306ab61f49894bd0e5570e79e5eb1686361b9e7aa82962

Observation f5fb8b73-af58-4d6a-8384-f33d428eaa2c · outbound

This paper cites Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T17:12:50.036264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:12:50.036264Z digest=sha256:5f7daae0eaf0eb6a6b3a44ba3415ae8c3b1c7bcab13718b1dd7c71fa5c7964cc

Observation 7b975f1a-9756-4d15-835b-6a8c6bdd9c23 · outbound

This paper cites an unresolved cited work.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:12:50.299003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.079636Z digest=sha256:663a78253d0458bd5663f37b3f030434d7520fa74484e9c030e45e67a7938dfb

Observation e3458e1e-f95a-47bb-b2e0-17f38876750c · outbound

This paper cites an unresolved cited work.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:12:50.283385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.084999Z digest=sha256:0e57c9424cb7a9a682a29c3c146b5c6439f1a222d5c755659e073590ad8f4d3c

Observation 25d0071c-688f-4644-bf9d-99e1a81b9871 · outbound

This paper cites an unresolved cited work.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:12:50.266234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.090967Z digest=sha256:5f7d8c587a1066ce4a2cd10a6297807a3117fe013d1622d953a933c9df3deedf

Observation 8ccb46f6-b2aa-4a3e-a6d8-bfef35b586ba · outbound

This paper cites an unresolved cited work.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:12:50.246788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.096397Z digest=sha256:ad57f948ce2a4cb1a07c28d933f40ef481fa791208e079aa323f3346e6635b23

Observation b8369cb2-98f7-4032-92df-70c3c000c135 · outbound

This paper cites Advanced Ma- chine Learning with Python.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Advanced Ma- chine Learning with Python

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:12:50.228243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.101864Z digest=sha256:d40ca70e05f6b4c6a654e284d7d018336773501bc4e2cbb7b30d0ce31c820e9c

Observation 16244231-390b-45d0-9545-c3b5449a6880 · outbound

This paper cites an unresolved cited work.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:12:50.315248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.073547Z digest=sha256:2181f71db52af8ff95c350eff20fc0c2cd92a8b56d273684474d53c90cfa1896

Observation 76e29ae5-9143-453c-9fd2-99149b08efd4 · outbound

This paper cites ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming.

Styleclone: Face Stylization with Diffusion Based Data Augmentation ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-15T17:12:50.042441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:12:50.042441Z digest=sha256:52f4e79f29922cdc99fa8dbb91233acdbcd43d11e865d9ade4b21fdbc36f34b2

Observation 1f8b85f0-1f11-4b11-8f18-28a4c2a56281 · outbound

This paper cites AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation.

Styleclone: Face Stylization with Diffusion Based Data Augmentation AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-15T17:12:50.055138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:12:50.055138Z digest=sha256:10609e207683d8e03b194ea8899c8be44a5fc75d2639c133765a19e6126c6943

Observation 8fcc48cc-3402-47ee-85ba-9f9781763b70 · outbound

This paper cites GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts.

Styleclone: Face Stylization with Diffusion Based Data Augmentation GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-15T17:12:50.049093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:12:50.049093Z digest=sha256:b8edf0b19053b4cfff3ab5c9b3fd1e2edf842ed0e4529703c5351fdefdc2545f

Observation 1fc98634-72fd-4702-88b7-457f6c790d4a · outbound

This paper cites Regenerate the transformed data to make them more dissimilar to the original data and so that their similarity score with the original data is much lower than 0.85.

Styleclone: Face Stylization with Diffusion Based Data Augmentation Regenerate the transformed data to make them more dissimilar to the original data and so that their similarity score with the original data is much lower than 0.85

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:12:50.351531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T17:12:50.061515Z digest=sha256:48d276c776ed2f47ead3a848bb84b50c0db223e4e94d15013b83d0671aacb9ea

Observation 493d1422-cfcb-44a9-9338-7f7fa88bdce3 · outbound

This paper cites A Survey of Data Augmentation Approaches for NLP.

Styleclone: Face Stylization with Diffusion Based Data Augmentation A Survey of Data Augmentation Approaches for NLP

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T17:12:50.029454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:12:50.029454Z digest=sha256:b880db08a1a9a2ea5ced4cdfe3a07ab93cff42764b90fba4b00e440db4dfb66b

Pith citing papers

No inbound Pith citation observations are available.