Paper Citation Record · LEDGER

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning

As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2505.24360.

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

pith.paper-citation-record.v1
2505.24360 v3

Coverage vector

measured 55 of 55 reference resolution

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measured 56 of 56 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T07:03:08.655446Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-29T07:03:12.641768Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

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Outbound references

Observation 3ef46fd8-58ee-4217-a33f-2e628c6ae624 · outbound

This paper cites Language mod- els can explain neurons in language models.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Language mod- els can explain neurons in language models

Reference 1

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

Reference 2

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This paper cites Towards monosemanticity: Decomposing language mod- els with dictionary learning.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Towards monosemanticity: Decomposing language mod- els with dictionary learning

Reference 3

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This paper cites Thread: Circuits.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Thread: Circuits

Reference 4

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This paper cites Extracting Training Data from Diffusion Models.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Extracting Training Data from Diffusion Models

Reference 5

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Activation atlas

Reference 6

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This paper cites Improving Steering Vectors by Targeting Sparse Autoencoder Features.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 7

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This paper cites Be- yond surface statistics: Scene representations in a latent dif- fusion model, 2023.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Be- yond surface statistics: Scene representations in a latent dif- fusion model, 2023

Reference 8

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This paper cites A Synthetic Modal Generation of Additive Manufacturing Roughness Surfaces from Images.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning A Synthetic Modal Generation of Additive Manufacturing Roughness Surfaces from Images

Reference 9

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This paper cites Saeuron: Interpretable concept unlearning in diffusion models with sparse autoen- coders, 2025.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Saeuron: Interpretable concept unlearning in diffusion models with sparse autoen- coders, 2025

Reference 10

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This paper cites Interpreting and steering features in images.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Interpreting and steering features in images

Reference 11

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Observation a092ef3f-b18b-49f4-9641-f9413dc0b11d · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Qlora: Efficient finetuning of quantized llms,

Reference 12

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This paper cites Toy models of superposition.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Toy models of superposition

Reference 13

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This paper cites Scaling rectified flow trans- formers for high-resolution image synthesis, 2024.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Scaling rectified flow trans- formers for high-resolution image synthesis, 2024

Reference 14

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This paper cites Towards multimodal interpretability: Learning sparse interpretable features in vision transformers.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Towards multimodal interpretability: Learning sparse interpretable features in vision transformers

Reference 15

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This paper cites Concept sliders: Lora adaptors for precise control in diffusion models, 2023.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Concept sliders: Lora adaptors for precise control in diffusion models, 2023

Reference 16

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Observation 210c5085-d87b-46cc-a40a-373cc3c0b647 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Scaling and evaluating sparse autoencoders

Reference 17

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This paper cites Sparse autoencoders can interpret randomly ini- tialized transformers, 2025.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Sparse autoencoders can interpret randomly ini- tialized transformers, 2025

Reference 18

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Observation 38dcfa19-8126-458b-bbe7-7c350119315c · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Denoising Diffusion Probabilistic Models

Reference 19

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This paper cites Arbitrary style transfer in real-time with adaptive instance normalization, 2017.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Arbitrary style transfer in real-time with adaptive instance normalization, 2017

Reference 20

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Sparse autoencoders find highly interpretable features in language models

Reference 21

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

Reference 22

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Understanding and steering Llama 3, 2024

Reference 23

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Concept steerers: Leveraging k-sparse autoencoders for controllable genera- tions, 2025

Reference 24

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Revelio: Interpreting and leveraging semantic information in diffusion models, 2024

Reference 25

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This paper cites Bert busters: Outlier dimensions that dis- rupt transformers, 2021.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Bert busters: Outlier dimensions that dis- rupt transformers, 2021

Reference 26

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Instrumenting llm model internals in jax,

Reference 27

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Diffusion models already have a semantic latent space, 2023

Reference 28

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

Reference 29

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning The remark- able robustness of llms: Stages of inference?, 2024

Reference 30

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models

Reference 31

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Sparse crosscoders for cross-layer features and model diff- ing

Reference 32

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

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This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow, 2022.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Flow straight and fast: Learning to generate and transfer data with rectified flow, 2022

Reference 34

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Sparse autoencoder

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Shortform comment on sae locality

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Steering Language Model Refusal with Sparse Autoencoders

Reference 37

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unsupervised discovery of semantic latent directions in diffusion models, 2023

Reference 38

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Scalable diffusion models with transformers, 2023

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Jumping ahead: Improving reconstruction fi- delity with jumprelu sparse autoencoders, 2024

Reference 40

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning U-net: Convolutional networks for biomedical image segmentation,

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Adversarial diffusion distillation, 2023

Reference 42

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning A multimodal automated interpretability agent, 2025

Reference 43

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models

Reference 44

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Taking fea- tures out of superposition with sparse autoencoders

Reference 45

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Replacing sae encoders with inference-time optimisation, 2024

Reference 46

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Denois- ing diffusion implicit models

Reference 47

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unpacking sdxl turbo: Interpreting text-to-image models with sparse au- toencoders, 2024

Reference 48

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Steering Language Models With Activation Engineering

Reference 49

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 50

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning A general protocol to probe large vision models for 3d physical understanding, 2024

Reference 51

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This paper cites Why are adaptive methods good for attention models?,.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Why are adaptive methods good for attention models?,

Reference 52

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This paper cites Adding conditional control to text-to-image diffusion models, 2023.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Adding conditional control to text-to-image diffusion models, 2023

Reference 53

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Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

Reference 2011

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This paper cites an unresolved cited work.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Unresolved cited work

Reference 2023

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Pith citing papers

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Robust and Generalizable Safety Steering for Text-to-Image Diffusion Transformers cites this paper.

Robust and Generalizable Safety Steering for Text-to-Image Diffusion Transformers Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning

Reference 40

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