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Paper Citation Record · LEDGER

Styleclone: Face Stylization with Diffusion Based Data Augmentation

As of 16 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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.068231Z digest=sha256:e1111b1d6144d525ff59cf2842ad58c9380ccd241840a995fc4936d485d320d4

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:ca4fdab45c2184ca2b9af02960870dee196986fe451845772d89185bc4cdc21d

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.079636Z digest=sha256:595e46325180050a47a7367d6fa9c828f7df9dd8e3bdcda9ea180116dcc5984b

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.084999Z digest=sha256:3781247afcfe9f7a2a2e45fff792d95cdc5c4c2c345a8762b56b47afb835127e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.090967Z digest=sha256:050894d3295da749ca2d15bd926214fbcaad86ca97c079f98222191b3f3c1910

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.096397Z digest=sha256:d5d282ed63434a41b4dd0f0b0ed20e65f11145597c744de32b80a10d70de02b1

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.101864Z digest=sha256:e4ebf1e661e60fea85f6d5d7bf2837702eb00a7b15f59faa0a387013412644c7

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.073547Z digest=sha256:eae9efe17c5ffbe81cddd5ab2ded2bf98f80d370752d9be4c1126a184938099b

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=sha256:0dc1384257642afda7613c057767ab6ee3082fada117e86e76815d5a58e809c5

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=sha256:4f72c652fdafbb1f8896f2417ee2882a504d4ed95bdbfefa586ef05fa0bceb46

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:cbfba94cfdaae2d6649ca989855702ccecfbfb91c810b953ef07c1c4b5289d4f

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:12:50.061515Z digest=sha256:8fa0580666ac0e42ecf1f84707b05e05bd60687f12c22a52a29b974ad71d371c

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=sha256:617ca25a086fa44ccf5007a43db698322fe6d791b70b334b0680403ded11a0d4

Pith citing papers

No inbound Pith citation observations are available.