Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T17:33:11.125337Z
Paper Citation Record · LEDGER
Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation
As of 9 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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.