Paper Citation Record · LEDGER

Multimodal datasets: misogyny, pornography, and malignant stereotypes

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 51 inbound Pith citation observations for arXiv:2110.01963.

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pith.paper-citation-record.v1
2110.01963 v1

Coverage vector

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One-hop event checks from named stored sources.

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measured 51 of 51 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 1 of 1 external citation measurements

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External citation measurements

151
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Outbound references

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Pith citing papers

Observation 8a702dd3-72b0-4dc0-a81e-2532b8f02fac · inbound

GPT-NeoX-20B: An Open-Source Autoregressive Language Model cites this paper.

GPT-NeoX-20B: An Open-Source Autoregressive Language Model Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 12

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Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding cites this paper.

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Scaling Autoregressive Models for Content-Rich Text-to-Image Generation cites this paper.

Scaling Autoregressive Models for Content-Rich Text-to-Image Generation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 100

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Observation a74a9a40-9c32-4c00-b5ce-b74cce57813a · inbound

DreamFusion: Text-to-3D using 2D Diffusion cites this paper.

DreamFusion: Text-to-3D using 2D Diffusion Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 94

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Imagen Video: High Definition Video Generation with Diffusion Models cites this paper.

Imagen Video: High Definition Video Generation with Diffusion Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 3

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Observation 637864f5-cd84-4fb1-a845-7f734d105460 · inbound

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model cites this paper.

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 206

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Observation bc6cd989-0ad2-4b44-afd5-32472df02253 · inbound

MagicVideo: Efficient Video Generation With Latent Diffusion Models cites this paper.

MagicVideo: Efficient Video Generation With Latent Diffusion Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Observation 10e4aced-479b-43a5-a42a-2384127680c1 · inbound

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation cites this paper.

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 135

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Observation 7175bde7-1762-4ece-9fe9-37fb830716ed · inbound

Quantifying Geospatial in the Common Crawl Corpus cites this paper.

Quantifying Geospatial in the Common Crawl Corpus Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 5

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Observation 08f58c45-2b9c-468b-9d8e-ce98539d0300 · inbound

Safe Text-to-Image Generation: Simply Sanitize the Prompt Embedding cites this paper.

Safe Text-to-Image Generation: Simply Sanitize the Prompt Embedding Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Observation 0dc4dd10-06d2-418a-9e26-1e40ff1f4e50 · inbound

Provable unlearning in topic modeling and downstream tasks cites this paper.

Provable unlearning in topic modeling and downstream tasks Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 5

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CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models cites this paper.

CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 52

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When Image Generation Goes Wrong: A Safety Analysis of Stable Diffusion Models cites this paper.

When Image Generation Goes Wrong: A Safety Analysis of Stable Diffusion Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 7

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Understanding Bias in Large-Scale Visual Datasets cites this paper.

Understanding Bias in Large-Scale Visual Datasets Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 6

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Observation b4800331-9007-42f3-acb6-dd425f93b2a0 · inbound

Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters cites this paper.

Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 9

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Observation 12001a36-45c2-481e-ba93-b4a44767bdbd · inbound

Bridging the Data Provenance Gap Across Text, Speech and Video cites this paper.

Bridging the Data Provenance Gap Across Text, Speech and Video Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 35

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Focus-N-Fix: Region-Aware Fine-Tuning for Text-to-Image Generation cites this paper.

Focus-N-Fix: Region-Aware Fine-Tuning for Text-to-Image Generation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 5

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MASS: Overcoming Language Bias in Image-Text Matching cites this paper.

MASS: Overcoming Language Bias in Image-Text Matching Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 8

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The Human Labour of Data Work: Capturing Cultural Diversity through World Wide Dishes cites this paper.

The Human Labour of Data Work: Capturing Cultural Diversity through World Wide Dishes Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 17

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Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 19

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Scaling Pre-training to One Hundred Billion Data for Vision Language Models cites this paper.

Scaling Pre-training to One Hundred Billion Data for Vision Language Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 11

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Observation e876bcb0-f313-40c4-bbae-6e447158f201 · inbound

Diffusion Models Through a Global Lens: Are They Culturally Inclusive? cites this paper.

Diffusion Models Through a Global Lens: Are They Culturally Inclusive? Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 2023

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Deepfakes on Demand: the rise of accessible non-consensual deepfake image generators cites this paper.

Deepfakes on Demand: the rise of accessible non-consensual deepfake image generators Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 5

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare cites this paper.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Wisdom from Diversity: Bias Mitigation Through Hybrid Human-LLM Crowds cites this paper.

Wisdom from Diversity: Bias Mitigation Through Hybrid Human-LLM Crowds Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 2004

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Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models cites this paper.

Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 6

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TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation cites this paper.

TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 8

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Co-AttenDWG: Co-Attentive Dimension-Wise Gating and Expert Fusion for Multi-Modal Offensive Content Detection cites this paper.

Co-AttenDWG: Co-Attentive Dimension-Wise Gating and Expert Fusion for Multi-Modal Offensive Content Detection Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 23

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Observation 672c9ce1-be5e-4c62-91f4-05776827600b · inbound

Cultural Awareness in Vision-Language Models: A Cross-Country Exploration cites this paper.

Cultural Awareness in Vision-Language Models: A Cross-Country Exploration Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 3

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CuRe: Cultural Gaps in the Long Tail of Text-to-Image Systems cites this paper.

CuRe: Cultural Gaps in the Long Tail of Text-to-Image Systems Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 7

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A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset cites this paper.

A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 16

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Uncovering Conceptual Blindspots in Generative Image Models Using Sparse Autoencoders cites this paper.

Uncovering Conceptual Blindspots in Generative Image Models Using Sparse Autoencoders Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 100

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Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings cites this paper.

Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 6

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Understanding and evaluating computer vision models through the lens of counterfactuals cites this paper.

Understanding and evaluating computer vision models through the lens of counterfactuals Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 95

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Collective Recourse for Generative Urban Visualizations cites this paper.

Collective Recourse for Generative Urban Visualizations Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 3

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Observation d8b4d76c-3303-478a-8b18-b5e460561560 · inbound

Mapping the Stochastic Penal Colony cites this paper.

Mapping the Stochastic Penal Colony Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 12

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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How to Stop Playing Whack-a-Mole: Mapping the Ecosystem of Technologies Facilitating AI-Generated Non-Consensual Intimate Images cites this paper.

How to Stop Playing Whack-a-Mole: Mapping the Ecosystem of Technologies Facilitating AI-Generated Non-Consensual Intimate Images Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-21T14:00:12.791219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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SafeCtrl: Region-Aware Safety Control for Text-to-Image Diffusion via Detect-Then-Suppress cites this paper.

SafeCtrl: Region-Aware Safety Control for Text-to-Image Diffusion via Detect-Then-Suppress Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 3

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Dynamic Eraser for Guided Concept Erasure in Diffusion Models cites this paper.

Dynamic Eraser for Guided Concept Erasure in Diffusion Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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TextTeacher: What Can Language Teach About Images? cites this paper.

TextTeacher: What Can Language Teach About Images? Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 562a977a-5f90-4bb4-89eb-0edbd3bba817 · inbound

No Safe Dose: How Training Data Drives Unsafe Image Generation cites this paper.

No Safe Dose: How Training Data Drives Unsafe Image Generation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Toward a More Ethical Facial Age Estimation: A Generalized Zero-Shot Benchmark Without Training on Children's Data cites this paper.

Toward a More Ethical Facial Age Estimation: A Generalized Zero-Shot Benchmark Without Training on Children's Data Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dca4b65d-cfad-4f13-8247-31dfc0678337 · inbound

Toward a More Ethical Facial Age Estimation: A Generalized Zero-Shot Benchmark Without Training on Children's Data cites this paper.

Toward a More Ethical Facial Age Estimation: A Generalized Zero-Shot Benchmark Without Training on Children's Data Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 2019

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Observation e806c33a-736c-4478-802c-d7b3f672adc9 · inbound

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation cites this paper.

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:16:47.715121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4d1094a0-c318-4008-b817-8eb97cbc519c · inbound

The Market in the Model: Latent Diffusion as Neural Economy cites this paper.

The Market in the Model: Latent Diffusion as Neural Economy Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:49:24.784979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 833a421a-f909-45d9-91a4-057ad35eee25 · inbound

Co-occurring associated retained concepts in Diffusion Unlearning cites this paper.

Co-occurring associated retained concepts in Diffusion Unlearning Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8e6da459-7323-4733-8094-c0b384872140 · inbound

Selective Test-Time Debiasing for CLIP via Reward Gating cites this paper.

Selective Test-Time Debiasing for CLIP via Reward Gating Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:36:58.213809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5029c7de-6e67-47bb-b6fb-0b4b67c541cd · inbound

Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models cites this paper.

Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d6bb553b-cac2-47ed-9934-ab8b839c77e2 · inbound

Harm is not Universal: Community-Specific Toxicity Detection is Urgently Needed cites this paper.

Harm is not Universal: Community-Specific Toxicity Detection is Urgently Needed Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 150

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Observation b47c6d93-fc01-42a5-8796-a07032a6d50d · inbound

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning cites this paper.

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 247

Resolution: unresolved; no resolver link, observed 2026-08-16T00:36:02.809927Z

Source-reported events for the cited work

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Observation 20fcd595-00fd-4d9d-8d07-dafca106b09b · inbound

How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment cites this paper.

How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 7

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