Paper Citation Record · LEDGER

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods

As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2507.23010.

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

pith.paper-citation-record.v1
2507.23010 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:12:43.778984Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T10:22:04.455412Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T10:24:06.819543Z

Reference resolution

34 of 34 outbound references displayed

verified exact1
verified fuzzy15
unresolved18
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b4666bb-3dc0-431b-ac94-eea9afd54ebe · outbound

This paper cites GitHub - black-forest-labs/flux: Official inference repo for FLUX.1 models.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods GitHub - black-forest-labs/flux: Official inference repo for FLUX.1 models

Reference 1

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Observation 702430e7-ddde-4a7f-9978-ba6f357107e2 · outbound

This paper cites Towards Evaluating the Robustness of Neural Networks.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Towards Evaluating the Robustness of Neural Networks

Reference 2

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Observation 2b842ac9-a7ad-40b6-8ae2-698c4a9348c2 · outbound

This paper cites M´ ethode g´ en´ erale pour la r´ esolution des systemes d’´ equations simultan´ ees.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods M´ ethode g´ en´ erale pour la r´ esolution des systemes d’´ equations simultan´ ees

Reference 3

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Observation d3d73c09-2fd1-4c19-b356-d67f0cfe9af7 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Imagenet: A large-scale hierarchical image database

Reference 4

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Observation 1b5974e8-b7e1-42e1-99f8-127159b5f180 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 5

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Observation 5b04ff04-f201-4aab-bb9a-819fb8b45946 · outbound

This paper cites Adaptive subgradient meth- ods for online learning and stochastic optimization.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Adaptive subgradient meth- ods for online learning and stochastic optimization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:46.998027Z

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Observation 4924bfe0-3397-477a-bcb6-29d14bd9cd5c · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Explaining and Harnessing Adversarial Examples

Reference 7

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Observation 45d9c584-c1e2-4b07-b03d-971df4852c1b · outbound

This paper cites Signal estimation from modified short-time Fourier transform.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Signal estimation from modified short-time Fourier transform

Reference 8

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Observation d34bb4df-7039-4ca3-b4b5-36b95a5edc58 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 9

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Observation 310967cb-de3f-4244-834b-7d6a826c10c1 · outbound

This paper cites Neural networks for machine learning lecture 6a overview of mini-batch gradient descent.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Neural networks for machine learning lecture 6a overview of mini-batch gradient descent

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:46.655567Z

Source-reported events for the cited work

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Observation d1736f60-665d-4ced-93d2-2a3debabf8e8 · outbound

This paper cites Inversion of neural networks by gradient descent.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Inversion of neural networks by gradient descent

Reference 11

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Observation f8f2bf1f-0458-4b0a-bc97-6f792e72b05c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Adam: A Method for Stochastic Optimization

Reference 12

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Observation 36e9a592-4559-4741-a599-b23883a2d057 · outbound

This paper cites ImageNet Clas- sification with Deep Convolutional Neural Networks.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods ImageNet Clas- sification with Deep Convolutional Neural Networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:46.326241Z

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Observation ab77093d-a728-44e0-b59a-2389c8319f8e · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference 14

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Observation 8027fa4b-481c-4526-972c-e9916c12c0a3 · outbound

This paper cites Landscape Learning for Neural Network Inversion.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Landscape Learning for Neural Network Inversion

Reference 15

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Observation e89fc5ad-9d40-4bc0-a6c0-d3d958bf03a9 · outbound

This paper cites Decoupled Weight Decay Regularization.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Decoupled Weight Decay Regularization

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:46.130872Z

Source-reported events for the cited work

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Observation fc56bf93-c04a-47ad-8744-a3371e20c493 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 17

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Observation dc9d1627-5433-42d4-9cf7-0d1d867c7571 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Efficient Estimation of Word Representations in Vector Space

Reference 18

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Unresolved cited work

Reference 19

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Observation 656e5730-4ca0-4b3d-914d-85421f5a3854 · outbound

This paper cites Glove: Global Vectors for Word Representation.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Glove: Global Vectors for Word Representation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:45.807453Z

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Observation cee71972-b3c9-4360-8a7f-7cc5b121a850 · outbound

This paper cites Some methods of speeding up the convergence of iter- ation methods.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Some methods of speeding up the convergence of iter- ation methods

Reference 21

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Observation de2e7ff5-8b27-40e0-8154-ceecb86d9c27 · outbound

This paper cites Improving language understanding by generative pre- training.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Improving language understanding by generative pre- training

Reference 22

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Observation 240aa836-cac3-4fbb-8ea6-8677f437c147 · outbound

This paper cites Language models are unsupervised multitask learn- ers.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Language models are unsupervised multitask learn- ers

Reference 23

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Observation 965fedae-912b-4a28-88f9-092edd4ab9c8 · outbound

This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Robust Speech Recognition via Large-Scale Weak Supervision

Reference 24

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Observation 95f31781-7373-4e50-beaa-f1b7ada5053c · outbound

This paper cites GitHub - resemble-ai/chatterbox: SoTA open-source TTS.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods GitHub - resemble-ai/chatterbox: SoTA open-source TTS

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:45.029540Z

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Observation 3a8599e2-2f7f-48ec-94e5-2acc5e065263 · outbound

This paper cites Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs

Reference 26

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods A stochastic approximation method

Reference 27

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This paper cites Learning representations by back-propagating errors.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Learning representations by back-propagating errors

Reference 28

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Observation 10c6b81a-677a-43b1-b990-fa31d10d1fc3 · outbound

This paper cites Intriguing properties of neural networks.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Intriguing properties of neural networks

Reference 29

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods BERTScore: Evaluating Text Generation with BERT

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:12:44.492654Z

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Observation 3118cf28-1b12-4e17-9de8-20b0d4cd9b10 · outbound

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Unresolved cited work

Reference 1543

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Observation 28d081f2-8cc6-473b-a8f2-20ea0f9e852b · outbound

This paper cites Decoupled Weight Decay Regularization.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Decoupled Weight Decay Regularization

Reference 2019

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods BERTScore: Evaluating Text Generation with BERT

Reference 2020

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Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Unresolved cited work

Reference 2025

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Pith citing papers

Observation 9e9ac3cc-0312-4687-a458-bdf9a3708f7d · inbound

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning cites this paper.

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods

Reference 42

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