Paper Citation Record · LEDGER

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation

As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2502.05895.

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

pith.paper-citation-record.v1
2502.05895 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:33:11.125337Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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 exact0
verified fuzzy6
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01f4a7d1-741a-4e2a-bd87-ba449a1cd9f9 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.043839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae9e782-0396-4c9b-80f8-521039520423 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.070092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b6ccb7f-0791-4467-95b8-1e14a5f7ee8b · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.074881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 289913f6-ede7-42ad-adf5-0941dcc4cc93 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation High-resolution image synthesis with latent diffusion models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.403368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0411ce56-ec2e-4672-9021-eda79dcb21e8 · outbound

This paper cites Denoising Diffusion Implicit Models.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Denoising Diffusion Implicit Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.084338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dea28c6-188c-44b9-b9df-c438acaa4ae1 · outbound

This paper cites Enhancing Detail Preservation for Customized Text-to-Image Generation: A Regularization-Free Approach.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Enhancing Detail Preservation for Customized Text-to-Image Generation: A Regularization-Free Approach

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.093439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e38fb77-c109-439d-b6b2-32eb22f5d6d9 · outbound

This paper cites an unresolved cited work.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:33:11.373219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 25fc269d-3ca9-4a56-a1f3-4cdaddf1c3b7 · outbound

This paper cites The pseudo-token paradigm adjusts the text encoder to convert the concept token into the proper embedding for the diffusion model.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation The pseudo-token paradigm adjusts the text encoder to convert the concept token into the proper embedding for the diffusion model

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.357301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 65581217-0f5c-4757-ae92-548c65ab6d90 · outbound

This paper cites Such approaches usually require a small number of parameters to optimize but lose the visual features of the target concept.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Such approaches usually require a small number of parameters to optimize but lose the visual features of the target concept

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.340636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2b08f6a4-56eb-4587-96ee-7bcd6c8374bd · outbound

This paper cites This allows the model to learn the input concept with high accuracy, but the model due to overfitting may lose the ability to edit it when generated with different text prompts.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation This allows the model to learn the input concept with high accuracy, but the model due to overfitting may lose the ability to edit it when generated with different text prompts

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.325165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 901b9c0b-0282-47e1-a23c-527bb4e70ff4 · outbound

This paper cites an unresolved cited work.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:33:11.309559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e3048850-ccea-443e-9a0b-d6a593e9e4d8 · outbound

This paper cites an unresolved cited work.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:33:11.293719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a154f444-a61f-4e10-b30c-f54b83470fd3 · outbound

This paper cites Figure 25: The overall results of different sampling methods against main personalized generation baselines.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Figure 25: The overall results of different sampling methods against main personalized generation baselines

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.278643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation da2a1133-fc55-4bdf-91fa-fbf3055409f1 · outbound

This paper cites Key-locked rank one editing for text-to-image personalization.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Key-locked rank one editing for text-to-image personalization

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:33:11.388067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff29bd0c-d767-4c3d-a1fe-4fcd9b6ebbe1 · outbound

This paper cites Multi-concept customization of text-to-image diffusion.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Multi-concept customization of text-to-image diffusion

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.060202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b263e6a7-0fed-482f-b2f5-77028a7a243d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.055220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4adc0c30-2c4c-484d-b394-47a97275a983 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation Classifier-Free Diffusion Guidance

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.050040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc6298cc-e1fe-4488-ba12-065f7c85e52c · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation DINOv2: Learning Robust Visual Features without Supervision

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:11.065322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.