mlsanityData to 7 Oct 2026

On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook

arXiv 2307.16680 ↗First posted 31 Jul 2023cs.LG cs.AI cs.CLcited by 15

On the map: Diffusion models → Robustness, privacy and adversarial aspects

Abstract (arXiv)

Diffusion models and large language models have emerged as leading-edge generative models, revolutionizing various aspects of human life. However, the practical implementations of these models have also exposed inherent risks, bringing to the forefront their evil sides and sparking concerns regarding their trustworthiness. Despite the wealth of literature on this subject, a comprehensive survey specifically delving into the intersection of large-scale generative models and their trustworthiness remains largely absent. To bridge this gap, this paper investigates both the long-standing and emerging threats associated with these models across four fundamental dimensions: 1) privacy, 2) security, 3) fairness, and 4) responsibility. Based on the investigation results, we develop an extensive map outlining the trustworthiness of large generative models. After that, we provide practical recommendations and potential research directions for future secure applications equipped with large generative models, ultimately promoting the trustworthiness of the models and benefiting the society as a whole.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Placed in Robustness, privacy and adversarial aspects, one of 14 directions in Diffusion models. Builds on 211 of its 357 references that are in the map. First posted on arXiv 31 Jul 2023.

Builds on

211 of 357 references.

Closest ancestors · 19

Same direction, newest first

  1. 2023On the Robustness of Latent Diffusion Models14 Jun
  2. 2023VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models12 Jun
  3. 2023Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Models2 Jun
  4. 2023Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust31 May
  5. 2023Personalization as a Shortcut for Few-Shot Backdoor Attack against Text-to-Image Diffusion Models18 May
  6. 2023Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning7 May
  7. 2023A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion29 Mar
  8. 2023Ablating Concepts in Text-to-Image Diffusion Models23 Mar
  9. 2023A Recipe for Watermarking Diffusion Models17 Mar
  10. 2023Erasing Concepts from Diffusion Models13 Mar
  11. 2023TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targets10 Mar
  12. 2023Differentially Private Diffusion Models Generate Useful Synthetic Images27 Feb
7 more
  1. 2023Raising the Cost of Malicious AI-Powered Image Editing13 Feb
  2. 2023Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples9 Feb
  3. 2023Membership Inference Attacks against Diffusion Models7 Feb
  4. 2023Are Diffusion Models Vulnerable to Membership Inference Attacks?2 Feb
  5. 2023Extracting Training Data from Diffusion Models30 Jan
  6. 2023Membership Inference of Diffusion Models24 Jan
  7. 2022How to Backdoor Diffusion Models?11 Dec

Other references · 192

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2023GPT-4 Technical Reportcited by 18,132
  6. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  7. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  8. 2020Denoising Diffusion Implicit Modelscited by 9,655
  9. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  10. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  11. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  12. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
38 more
  1. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  2. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  5. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  6. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  7. 2019Parameter-Efficient Transfer Learning for NLPcited by 4,195
  8. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  9. 2023Let's Verify Step by Stepcited by 3,598
  10. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
  11. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  12. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
  13. 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
  14. 2016Deep Learning with Differential Privacycited by 2,682
  15. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  16. 2020Extracting Training Data from Large Language Modelscited by 2,144
  17. 2023Consistency Modelscited by 1,778
  18. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,565
  19. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  20. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,371
  21. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
  22. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,339
  23. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  24. 2021Improving language models by retrieving from trillions of tokenscited by 1,278
  25. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,259
  26. 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Modelcited by 1,259
  27. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  28. 2020RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Modelscited by 1,235
  29. 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
  30. 2022When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memoriescited by 1,103
  31. 2023LIMA: Less Is More for Alignmentcited by 1,080
  32. 2017BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chaincited by 1,052
  33. 2023ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generationcited by 1,010
  34. 2019Deep Leakage from Gradientscited by 1,004
  35. 2022Red Teaming Language Models with Language Modelscited by 983
  36. 2023Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMscited by 946
  37. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 934
  38. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 7; 2026: 5.

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  1. 2024Towards Trustworthy AI: A Review of Ethical and Robust Large Language Modelscited by 21
  2. 2024Replication in Visual Diffusion Models: A Survey and Outlookcited by 11
  3. 2025Generative AI in Transportation Planning: A Surveycited by 8
  4. 2026LSSF: Safety Alignment for Large Language Models through Low-Rank Safety Subspace Fusioncited by 8
  5. 2025CE-SDWV: Effective and Efficient Concept Erasure for Text-to-Image Diffusion Models via a Semantic-Driven Word Vocabularycited by 7
  6. 2025Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferencescited by 7
  7. 2024TorchOpera: A Compound AI System for LLM Safetycited by 4
  8. 2025A Short Survey on Small Reasoning Models: Training, Inference, Applications and Research Directionscited by 4
  9. 2026GenProve: Learning to Generate Text with Fine-Grained Provenancecited by 2
  10. 2025Comprehensive Evaluation and Analysis for NSFW Concept Erasure in Text-to-Image Diffusion Modelscited by 1
  11. 2025Comprehensive Assessment and Analysis for NSFW Content Erasure in Text-to-Image Diffusion Modelscited by 0
  12. 2025EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Modelscited by 0
3 more
  1. 2026Trustworthy deep domain adaptation for wearable photoplethysmography signal analysis with decision-theoretic uncertainty quantificationcited by 0
  2. 2026OverAct: Measuring and Mitigating Proactive Over-Authorization in LLM Tool-Calling Agentscited by 0
  3. 2026How the Audit Rule Shapes Faithful Factor Explanations in LLMscited by 0

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  2. 2025Responsible Diffusion: A Comprehensive Survey on Safety, Ethics, and Trust in Diffusion Models
  3. 2024MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
  4. 2025Mapping Trustworthiness in Large Language Models: A Bibliometric Analysis Bridging Theory to Practice
  5. 2026From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop
  6. 2025SciTrust 2.0: A Comprehensive Framework for Evaluating Trustworthiness of Large Language Models in Scientific Applications
  7. 2024More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
  8. 2026TrustLDM: Benchmarking Trustworthiness in Language Diffusion Models