mlsanityData to 7 Oct 2026

Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models

arXiv 2401.06102 ↗First posted 11 Jan 2024cs.CL cs.AI cs.LGcited by 225

Not on the map. Why?

Cited by 27 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Understanding the internal representations of large language models (LLMs) can help explain models' behavior and verify their alignment with human values. Given the capabilities of LLMs in generating human-understandable text, we propose leveraging the model itself to explain its internal representations in natural language. We introduce a framework called Patchscopes and show how it can be used to answer a wide range of questions about an LLM's computation. We show that many prior interpretability methods based on projecting representations into the vocabulary space and intervening on the LLM computation can be viewed as instances of this framework. Moreover, several of their shortcomings such as failure in inspecting early layers or lack of expressivity can be mitigated by Patchscopes. Beyond unifying prior inspection techniques, Patchscopes also opens up new possibilities such as using a more capable model to explain the representations of a smaller model, and multihop reasoning error correction.

Key facts. Cited by 225 papers in the map (data through 7 Oct 2026). Builds on 57 of its 72 references that are in the map. First posted on arXiv 11 Jan 2024.

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57 of 72 references.

References · 57

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50 most cited of 57 All 57 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 52; 2025: 83; 2026: 90.

225 papers.

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  1. 2024Mechanistic Interpretability for AI Safety -- A Reviewcited by 415
  2. 2024The Geometry of Categorical and Hierarchical Concepts in Large Language Modelscited by 151
  3. 2024Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lenscited by 139
  4. 2024A Practical Review of Mechanistic Interpretability for Transformer-Based Language Modelscited by 113
  5. 2024Automatically Interpreting Millions of Features in Large Language Modelscited by 106
  6. 2024Interpreting and Editing Vision-Language Representations to Mitigate Hallucinationscited by 103
  7. 2024A Primer on the Inner Workings of Transformer-based Language Modelscited by 83
  8. 2024Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queriescited by 78
  9. 2026Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Modelscited by 78
  10. 2024RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representationscited by 77
  11. 2025Do Multilingual LLMs Think In English?cited by 75
  12. 2024The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalitiescited by 69
38 more
  1. 2024SelfIE: Self-Interpretation of Large Language Model Embeddingscited by 63
  2. 2024Knowledge Circuits in Pretrained Transformerscited by 60
  3. 2024LoFiT: Localized Fine-tuning on LLM Representationscited by 56
  4. 2024Demystifying Verbatim Memorization in Large Language Modelscited by 55
  5. 2024Rebuilding ROME : Resolving Model Collapse during Sequential Model Editingcited by 50
  6. 2024Knowledge Mechanisms in Large Language Models: A Survey and Perspectivecited by 50
  7. 2024LatentQA: Teaching LLMs to Decode Activations Into Natural Languagecited by 49
  8. 2024Representation Surgery: Theory and Practice of Affine Steeringcited by 47
  9. 2024From Tokens to Words: On the Inner Lexicon of LLMscited by 46
  10. 2024Understanding and Patching Compositional Reasoning in LLMscited by 45
  11. 2024Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformerscited by 42
  12. 2025Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainerscited by 41
  13. 2024Who's asking? User personas and the mechanics of latent misalignmentcited by 40
  14. 2024Estimating Knowledge in Large Language Models Without Generating a Single Tokencited by 39
  15. 2024Mechanistic Understanding and Mitigation of Language Model Non-Factual Hallucinationscited by 38
  16. 2024Locate-then-edit for Multi-hop Factual Recall under Knowledge Editingcited by 36
  17. 2024Backward Lens: Projecting Language Model Gradients into the Vocabulary Spacecited by 30
  18. 2024One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Modelscited by 30
  19. 2025Pixels Versus Priors: Controlling Knowledge Priors in Vision-Language Models through Visual Counterfactscited by 30
  20. 2024Towards Unifying Interpretability and Control: Evaluation via Interventioncited by 28
  21. 2025Training Language Models to Explain Their Own Computationscited by 27
  22. 2024Do Large Language Models Perform Latent Multi-Hop Reasoning without Exploiting Shortcuts?cited by 26
  23. 2025The LLM Already Knows: Estimating LLM-Perceived Question Difficulty via Hidden Representationscited by 26
  24. 2024Attend First, Consolidate Later: On the Importance of Attention in Different LLM Layerscited by 25
  25. 2024On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMscited by 24
  26. 2025Mechanistic Interpretability of Emotion Inference in Large Language Modelscited by 24
  27. 2025Narrow Finetuning Leaves Clearly Readable Traces in Activation Differencescited by 24
  28. 2024Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixturecited by 22
  29. 2024Controllable Context Sensitivity and the Knob Behind Itcited by 22
  30. 2025LogitLens4LLMs: Extending Logit Lens Analysis to Modern Large Language Modelscited by 22
  31. 2025The Dual-Route Model of Inductioncited by 22
  32. 2024An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMscited by 20
  33. 2025Language-Specific Latent Process Hinders Cross-Lingual Performancecited by 20
  34. 2025Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipelinecited by 20
  35. 2025Localized Cultural Knowledge is Conserved and Controllable in Large Language Modelscited by 19
  36. 2025Representation Engineering for Large-Language Models: Survey and Research Challengescited by 18
  37. 2025AudioLens: A Closer Look at Auditory Attribute Perception of Large Audio-Language Modelscited by 18
  38. 2024Improved Generation of Adversarial Examples Against Safety-aligned LLMscited by 17

50 most cited of 225 All 225 (JSON)

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