Mechanistic Interpretability papers, 2023–2026

Key findings

• Mechanistic Interpretability went from 17 papers in 2023 to 138 in 2026, roughly 8.1x in three years.
• ICML publishes the most Mechanistic Interpretability work: 119 papers from 2023 to 2026, 38% of the four-venue total.
• The fastest-growing overlap is with Deep learning · large language models: papers tagged with both rose from 1 in 2023 to 23 in 2026.
• Among the 5 topics under Interpretability, it ranks #2 by 2026 paper count; the fastest grower in the group, Feature Attribution, is up 1.9x versus 8.1x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Mechanistic Interpretability Study of an Astronomical Foundation Model
• ICML 2026Contribution Weights: A Geometrical Analysis of Self-Attention Transformers
• ICLR 2026Circuit Insights: Towards Interpretability Beyond Activations
• CVPR 2026CIGMA Causal Information-Gain Mechanistic Attribution of Attention Heads in Vision
• NeurIPS 2025Beyond Components: Singular Vector-Based Interpretability of Transformer Circuits
• ICML 2025Algorithm Development in Neural Networks: Insights from the Streaming Parity Task
• ICLR 2025Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics
• CVPR 2025Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability
• NeurIPS 2024InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques
• ICML 2024Mechanistic Neural Networks for Scientific Machine Learning
• ICLR 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
• CVPR 2024SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology
• NeurIPS 2023A Logic for Expressing Log-Precision Transformers
• ICML 2023Mechanistic Mode Connectivity
• ICLR 2023Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small
• NeurIPS 2026Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish
• ICML 2026CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features
• ICLR 2026CLUE: Conflict-guided Localization for LLM Unlearning Framework
• CVPR 2026From Weights to Concepts Data-Free Interpretability of CLIP via Singular
• NeurIPS 2025Bigram Subnetworks: Mapping to Next Tokens in Transformer Language Models

All Mechanistic Interpretability papers

85 papers, page 1 of 2

1. NeurIPS 2026A Mechanistic Interpretability Study of an Astronomical Foundation Model
2. NeurIPS 2026A Unifying Perspective on Language Model Interpretability
3. NeurIPS 2026Assign and Add: A Mechanistic Study of Compositional Arithmetic
4. NeurIPS 2026Circuit-Level Knowledge Distillation for Large Language Models
5. NeurIPS 2026Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish
6. NeurIPS 2026Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift
7. NeurIPS 2026How Do Language Models Understand Tables? A Mechanistic Analysis of Cell Location
8. NeurIPS 2026How do Small Transformer Models Learn Hard Math Tasks?
9. NeurIPS 2026Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration
10. NeurIPS 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting
11. NeurIPS 2026On the Recall Scaling Laws in Mamba: A Theoretical and Mechanistic Study via Hashing
12. NeurIPS 2026Patching Up Circuit Learning on Images
13. NeurIPS 2026Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants
14. NeurIPS 2026Structural Support Certificates for Mechanistic Hypothesis Selection
15. NeurIPS 2026The parameters in weight-sparse transformers are interpretable
16. NeurIPS 2026The Unembedding Bottleneck: A Mechanistic Analysis of Single Digit Counting in LLMs
17. NeurIPS 2025A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning
18. NeurIPS 2025Angular Steering: Behavior Control via Rotation in Activation Space
19. NeurIPS 2025Attention Sinks: A 'Catch, Tag, Release' Mechanism for Embeddings
20. NeurIPS 2025Better Training Data Attribution via Better Inverse Hessian-Vector Products
21. NeurIPS 2025Beyond Components: Singular Vector-Based Interpretability of Transformer Circuits
22. NeurIPS 2025Bigram Subnetworks: Mapping to Next Tokens in Transformer Language Models
23. NeurIPS 2025Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework
24. NeurIPS 2025Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers
25. NeurIPS 2025Dense SAE Latents Are Features, Not Bugs
26. NeurIPS 2025DePass: Unified Feature Attributing by Simple Decomposed Forward Pass
27. NeurIPS 2025Detecting High-Stakes Interactions with Activation Probes
28. NeurIPS 2025Do different prompting methods yield a common task representation in language models?
29. NeurIPS 2025EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification
30. NeurIPS 2025FaCT: Faithful Concept Traces for Explaining Neural Network Decisions
31. NeurIPS 2025Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
32. NeurIPS 2025Improved Representation Steering for Language Models
33. NeurIPS 2025Interpreting Emergent Features in Deep Learning-based Side-channel Analysis
34. NeurIPS 2025Interpreting vision transformers via residual replacement model
35. NeurIPS 2025LLM Interpretability with Identifiable Temporal-Instantaneous Representation
36. NeurIPS 2025LLM Layers Immediately Correct Each Other
37. NeurIPS 2025Manipulating Feature Visualizations with Gradient Slingshots
38. NeurIPS 2025Mechanistic Interpretability of RNNs emulating Hidden Markov Models
39. NeurIPS 2025Mitigating Overthinking in Large Reasoning Models via Manifold Steering
40. NeurIPS 2025Pinpointing Attention-Causal Communication in Language Models
41. NeurIPS 2025Prompting as Scientific Inquiry
42. NeurIPS 2025Remarkable Robustness of LLMs: Stages of Inference?
43. NeurIPS 2025Rethinking Circuit Completeness in Language Models: AND, OR, and ADDER Gates
44. NeurIPS 2025Revising and Falsifying Sparse Autoencoder Feature Explanations
45. NeurIPS 2025Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs
46. NeurIPS 2025The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability?
47. NeurIPS 2025The Structure of Relation Decoding Linear Operators in Large Language Models
48. NeurIPS 2025Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
49. NeurIPS 2025Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning
50. NeurIPS 2025What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains

FAQ

How many Mechanistic Interpretability papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

311 in total: 17 in 2023, 49 in 2024, 107 in 2025, 138 in 2026.

How many Mechanistic Interpretability papers are at NeurIPS 2026?

NeurIPS 2026 has 16 Mechanistic Interpretability papers, versus 34 the year before.

How many Mechanistic Interpretability papers are at ICLR 2026?

ICLR 2026 has 46 Mechanistic Interpretability papers, versus 38 the year before.

How many Mechanistic Interpretability papers are at ICML 2026?

ICML 2026 has 74 Mechanistic Interpretability papers, versus 33 the year before.

How many Mechanistic Interpretability papers are at CVPR 2026?

CVPR 2026 has 2 Mechanistic Interpretability papers, versus 2 the year before.

Which conference publishes the most Mechanistic Interpretability papers?

ICML, with 119 papers from 2023 to 2026.