Paper Citation Record · LEDGER

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.14549.

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

pith.paper-citation-record.v1
2507.14549 v1

Coverage vector

measured 38 of 38 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-06T15:58:20.441340Z

measured 38 of 38 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation c9b2da90-10cd-41c3-808b-edbb90ea5fdf · outbound

This paper cites CoCoG: Controllable Visual Stimuli Generation based on Human Concept Representations.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions CoCoG: Controllable Visual Stimuli Generation based on Human Concept Representations

Reference 1

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This paper cites CoCoG-2: Controllable generation of visual stimuli for understanding human concept representation.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions CoCoG-2: Controllable generation of visual stimuli for understanding human concept representation

Reference 2

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This paper cites Human alignment of neural network representations.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Human alignment of neural network representations

Reference 3

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Observation c53acc01-49e2-4cdc-9752-c94350079e6b · outbound

This paper cites Dimensions underlying the representational alignment of deep neural networks with humans.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Dimensions underlying the representational alignment of deep neural networks with humans

Reference 4

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Observation 6a8a20ec-0da3-426c-8ed3-15821014e119 · outbound

This paper cites Revealing interpretable object representations from human behavior.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Revealing interpretable object representations from human behavior

Reference 5

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Observation 4bb2534d-ef3f-4331-963a-6158ef447820 · outbound

This paper cites Revealing the multidimensional mental representations of natural objects underlying human similarity judgements,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Revealing the multidimensional mental representations of natural objects underlying human similarity judgements,

Reference 6

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Observation ce53fa27-625d-4d1f-a371-218868217359 · outbound

This paper cites Vice: Variational interpretable concept embed- dings,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Vice: Variational interpretable concept embed- dings,

Reference 7

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Observation d6ab2d4a-972f-4a16-84fb-088cd85833a1 · outbound

This paper cites The face of noncompliance in family interaction,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions The face of noncompliance in family interaction,

Reference 8

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Observation 0238268c-d90a-4612-af5c-fae0e08d16df · outbound

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

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 9

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Observation deffe7dd-bcd3-4ad0-b81d-6f857e2423d7 · outbound

This paper cites Subtle adversarial image manipulations influence both human and machine perception,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Subtle adversarial image manipulations influence both human and machine perception,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:25.858027Z

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Observation 5e6211ef-99c4-4b75-863e-8885409145fd · outbound

This paper cites Strong and precise modulation of human percepts via robustified anns,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Strong and precise modulation of human percepts via robustified anns,

Reference 11

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Observation 2fafca4a-c922-4004-9d85-4921ca6c6a82 · outbound

This paper cites Model metamers reveal divergent invariances between biological and artificial neural networks,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Model metamers reveal divergent invariances between biological and artificial neural networks,

Reference 12

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Observation f176b25e-f4fd-42bb-be79-b287968d06f3 · outbound

This paper cites Controversial stimuli: Pitting neural networks against each other as models of human cognition,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Controversial stimuli: Pitting neural networks against each other as models of human cognition,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:25.305920Z

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Observation 9daefb2f-c74d-4edd-96cb-1c102f73a466 · outbound

This paper cites Testing the limits of natural language models for predicting human language judgements,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Testing the limits of natural language models for predicting human language judgements,

Reference 14

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Observation 0daa2693-78f8-4776-a44a-17eeea908132 · outbound

This paper cites Metamers of neural networks reveal divergence from human perceptual systems,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Metamers of neural networks reveal divergence from human perceptual systems,

Reference 15

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Observation d6efdf6d-65b7-4611-920f-6c3330c67210 · outbound

This paper cites Measuring representational robustness of neural networks through shared invariances,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Measuring representational robustness of neural networks through shared invariances,

Reference 16

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Observation e1a15b03-dc28-40e0-9b46-7865e652265a · outbound

This paper cites Do invariances in deep neural networks align with human perception?.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Do invariances in deep neural networks align with human perception?

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:24.593834Z

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Observation 354a258f-054c-47ec-a5e3-702dfec6a4c2 · outbound

This paper cites DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Reference 18

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This paper cites Aligning Machine and Human Visual Representations across Abstraction Levels.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Aligning Machine and Human Visual Representations across Abstraction Levels

Reference 19

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This paper cites When Does Perceptual Alignment Benefit Vision Representations?.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions When Does Perceptual Alignment Benefit Vision Representations?

Reference 20

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Observation 2f7ca0b8-1c75-460f-a2a6-bb7c07fd2c83 · outbound

This paper cites Adversarial counterfactual visual explanations,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Adversarial counterfactual visual explanations,

Reference 21

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Observation f3e6c7e7-8036-4404-ac6b-90f69f13ba0f · outbound

This paper cites Advdiffuser: Natural adversarial example synthesis with diffusion models,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Advdiffuser: Natural adversarial example synthesis with diffusion models,

Reference 22

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Observation b0ef5df4-9cdd-41f8-bb08-25ae0bf4e2bf · outbound

This paper cites Diffusion models for counterfac- tual explanations,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Diffusion models for counterfac- tual explanations,

Reference 23

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Observation 5b5520ec-30bf-4b10-8293-f6ce1edb339e · outbound

This paper cites Diffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative Evaluation.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Diffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative Evaluation

Reference 24

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This paper cites Dreamr: Diffusion-driven counterfactual explanation for functional mri,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Dreamr: Diffusion-driven counterfactual explanation for functional mri,

Reference 25

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This paper cites Freedom: Training- free energy-guided conditional diffusion model,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Freedom: Training- free energy-guided conditional diffusion model,

Reference 26

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This paper cites Elucidating The Design Space of Classifier-Guided Diffusion Generation.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Elucidating The Design Space of Classifier-Guided Diffusion Generation

Reference 27

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This paper cites Guidance with Spherical Gaussian Constraint for Conditional Diffusion.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Guidance with Spherical Gaussian Constraint for Conditional Diffusion

Reference 28

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Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Facial action coding system,

Reference 29

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This paper cites Universals and cultural variations in 22 emotional expressions across five cultures.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Universals and cultural variations in 22 emotional expressions across five cultures

Reference 30

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This paper cites Emotional expression: Advances in basic emotion theory,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Emotional expression: Advances in basic emotion theory,

Reference 31

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This paper cites Facial expressions of emotion,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Facial expressions of emotion,

Reference 32

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This paper cites Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time,

Reference 33

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This paper cites Testing, explaining, and exploring models of facial expressions of emotions,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Testing, explaining, and exploring models of facial expressions of emotions,

Reference 34

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Observation 4afe8c8e-a77f-4452-985d-7e42cba778a1 · outbound

This paper cites Generative Adversarial Networks.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Generative Adversarial Networks

Reference 35

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This paper cites Cocog-2: Controllable generation of visual stimuli for understanding human concept representation,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Cocog-2: Controllable generation of visual stimuli for understanding human concept representation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:22.360526Z

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Observation bc776b6a-cceb-4c10-9eb9-1897e82e3c21 · outbound

This paper cites Diffusion- based visual counterfactual explanations-towards systematic quantitative evaluation,.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions Diffusion- based visual counterfactual explanations-towards systematic quantitative evaluation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:22.264043Z

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This paper cites All are Worth Words: A ViT Backbone for Diffusion Models.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering Human Perceptual Variability on Facial Expressions All are Worth Words: A ViT Backbone for Diffusion Models

Reference 38

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