NeurIPS 2025PastInterpretability
Mechanistic Interpretability Workshop at NeurIPS 2025
Mech Interp Workshop (NeurIPS 2025)
- Submission deadline
- Aug 23, 2025, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (187)
Fetched from OpenReview (v2) on 2026-06-10.
Activation Steering in Generative Settings via Contrastive Causal Mediation Analysis
Activation Transport Operators
Adaptive Task Vectors for Large Language Models
Adversarial Attacks Leverage Interference Between Features in Superposition
Adversarial Examples Are Not Bugs, They Are Superposition
Analyzing and Improving Chain-of-Thought Monitorability Through Information Theory
Angular Steering: Behavior Control via Rotation in Activation Space
Attention Layers Add Into Low-Dimensional Residual Subspaces
Attention Pattern Discovery at Scale
Attributing Response to Context: A Jensen–Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation
Automated Detection of Visual Attribute Reliance with a Self-Reflective Agent
Automatically Finding Rule-Based Neurons in OthelloGPT
Base Models Know How to Reason, Thinking Models Learn When
Better Hessians Matter: Studying the Impact of Curvature Approximations in Influence Functions
Better World Models Can Lead to Better Post-Training Performance
Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality
Beyond the Final Layer: Intermediate Representations for Better Multilingual Calibration in Large Language Models
Bilinear Convolution Decomposition for Causal RL Interpretability
Bimodality of Sparse Autoencoder Features is Still There and Can Be Fixed
Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators
Can Interpretation Predict Behavior on Unseen Data?
Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework
Causal Discovery and Inference through Next-Token Prediction
Centroid Affinity: How Deep Networks Represent Features
Circuit-Tracer: A New Library for Finding Feature Circuits
Comparing Clinical and General LLMs on Knowledge Boundaries and Robustness
Composable Sparse Subnetworks via Maximum-Entropy Principle
Compressed Computation is (probably) not Computation in Superposition
Compressed Computation: Dense Circuits in a Toy Model of the Universal-AND Problem
Context Matters: Analyzing the Generalizability of Linear Probing and Steering Across Diverse Scenarios
ContextBench: Modifying Contexts for Targeted Latent Activation and Behaviour Elicitation
Control and Predictivity in Neural Interpretability
Controlling Vision–Language–Action Policies through Sparse Latent Directions
Convergent Linear Representations of Emergent Misalignment
Correlations in the Data Lead to Semantically Rich Feature Geometry Under Superposition
Cross-Architecture Model Diffing with Crosscoders: Unsupervised Discovery of Differences Between LLMs
Death by a Thousand Directions: Exploring the Geometry of Harmfulness in LLMs through Subconcept Probing
Decomposing Attention To Find Context-Sensitive Neurons
Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning
Decomposition of Small Transformer Models
Demystifying Cipher-Following in Large Language Models via Activation Analysis
Dense SAE Latents Are Features, Not Bugs
Detecting and Characterizing Planning in Language Models
Detecting Motivated Reasoning in the Internal Representations of Language Models
Discovering Transformer Circuits via a Hybrid Attribution and Pruning Framework
Do Natural Language Descriptions of Model Activations Convey Privileged Information?
Do We Always Need Sampling? Eliciting Numerical Predictive Distributions of LLMs Without Auto-Regression
Does FLUX Know What It’s Writing?
Don't Believe the Belief Hype!
Dual Mechanisms of Value Expression: Decomposing Intrinsic and Prompted Values in Language Models
Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP
Eliciting Secret Knowledge from Language Models
Emergence of Linear Truth Encodings in Language Models
Emergent Specialization: Rare Token Neurons in Language Models
Emergent World Beliefs: Exploring Transformers in Stochastic Games
Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models
Enforcing Orderedness in SAEs to Improve Feature Consistency
Entity Multiplexing Through Activation Strength: Understanding goals in A Maze Solving Agent
Equivalent Linear Mappings of Large Language Models
Evaluating Explanatory Evaluations: An Explanatory Virtues Framework for Mechanistic Interpretability
Evaluating SAE interpretability without explanations
Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability
False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize
Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders
Feature interactions in sparse crosscoders from compact proofs
Feature-Guided SAE Steering for Refusal-Rate Control using Contrasting Prompts
Finding Manifolds with Bilinear Autoencoders
Fluid Reasoning Representations
From Black-box to Causal-box: Towards Building More Interpretable Models
From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits
From Local to Contextually-Enriched Local Representations: A Mechanism for Holistic Processing in DINOv2 ViTs
From Narrow Unlearning to Emergent Misalignment: Causes, Consequences, and Containment in LLMs
From Tokens to Semantics: The Emergence and Stabilization of Polysemanticity in Language Models
Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition
Group Equivariance Meets Mechanistic Interpretability: Equivariant Sparse Autoencoders
Hallucination Reduction with CASAL: Contrastive Activation Steering for Amortized Learning
Head Pursuit: Probing Attention Specialization in Multimodal Transformers
Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task
Higher-Order Component Attribution via Kolmogorov–Arnold Networks
How does Mamba Perform Associative Recall? A Mechanistic Study
Instruction Following by Boosting Attention of Large Language Models
InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation
Interpretability at the Network Level: Prior-Guided Drift Diffusion for Neural Circuit Analysis
Interpretability for Time Series Transformers using A Concept Bottleneck Framework
Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
Interpreting Attention Heads for Image-to-Text Information Flow in Large Vision–Language Models
Interpreting ResNet-based CLIP via Neuron-Attention Decomposition
Interpreting Vision Grounding in Vision-Language Models: A Case Study in Coordinate Prediction
Iterative Inference in a Chess-Playing Neural Network
Just-in-time and distributed task representations in language models
Language Models use Lookbacks to Track Beliefs
Latent Crystallographic Microscope: Probing the Emergent Crystallographic Knowledge in Large Language Models
Learned Structure in Cartridges: Keys as Shareable Routers in Self-Studied Representations
Learning Interpretable Features in Audio Latent Spaces via Sparse Autoencoders
Learning to Steer: Input-dependent Steering for Multimodal LLMs
LLM Pretraining with Continuous Concepts
LLM Probing with Contrastive Eigenproblems: Improving Understanding and Applicability of CCS
Localizing Reasoning Training-Induced Changes in Large Language Models
Looking into Black Box Code Language Models
Mapping Faithful Reasoning in Language Models
Measuring Sparse Autoencoder Feature Sensitivity
Mechanistic Evaluation of Transformers and State-Space Models
Mechanistic evidence that motif-gated domain recognition drives contact prediction in protein language models
Mechanistic Interpretability as Statistical Estimation: A Variance Analysis of EAP-IG
Mitigating Emergent Misalignment with Data Attribution
Mitigating Sycophancy in Language Models via Sparse Activation Fusion and Multi-Layer Activation Steering
Model Organisms for Emergent Misalignment
Motifs in Attention Patterns of Large Language Models
Multimodal Concept Bottleneck Models
Multiple Streams of Knowledge Retrieval: Enriching and Recalling in Transformers
Narrow Finetuning Leaves Clearly Readable Traces in the Activation Differences
Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution
nnterp: A Standardized Interface for Mechanistic Interpretability of Transformers
On the Geometry and Topology of Neural Circuits for Modular Addition
On the Limits of Linear Representation Hypotheses in Large Language Models: A Dynamical Systems Analysis
Open-Vocabulary Natural-Language Explanations of LLM Activations via Soft Prompts
OpenMAIA: a Multimodal Automated Interpretability Agent based on open-source models
Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning
Path Channels and Plan Extension Kernels: a Mechanistic Description of Planning in a Sokoban RNN
Physics Steering: Causal Control of Cross-Domain Concepts in a Physics Foundation Model
PII Jailbreaking in LLMs via Activation Steering Reveals Personal Information Leakage
Pinpointing Attention-Causal Communication in Language Models
Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs
Predicting Weak-to-Strong Generalization from Latent Representations
Probing by Analogy: Decomposing Probes into Activations for Better Interpretability and Inter-Model Generalization
Quiet Feature Learning in Algorithmic Tasks
Rank-1 LoRAs Encode Interpretable Reasoning Signals
ReFIne: A Framework for Trustworthy Large Reasoning Models with Reliability, Faithfulness, and Interpretability
ReflCtrl: Controlling LLM Reflection via Representation Engineering
RelP: Faithful and Efficient Circuit Discovery in Language Models via Relevance Patching
Representation Similarity Reveals Implicit Layer Grouping in Neural Networks
Rethinking Crowd-Sourced Evaluation of Neuron Explanations
Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone
Reverse Engineering a Stateful Reasoning Circuit
Reverse-Engineering Memory in DreamerV3: From Sparse Representations to Functional Circuits
RippleBench: Capturing Ripple Effects by Leveraging Existing Knowledge Repositories
RL-Obfuscation: Can Language Models Learn to Evade Latent-Space Monitors?
Robustly Improving LLM Fairness in Realistic Settings via Interpretability
SAE-ception: Iteratively Using Sparse Autoencoders as a Training Signal
Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs
Scratchpad Thinking: Alternation Between Storage and Computation in Latent Reasoning Models
Shared Memorization Structures in Transformers Revealed by Loss Curvature
Shared Parameter Subspaces and Cross-Task Linearity in Emergently Misaligned Behaviour
Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence
Small Vectors, Big Effects: A Mechanistic Study of RL-Induced Reasoning via Steering Vectors
Some Attention is All You Need for Retrieval
Sparse Autoencoders Trained on the Same Data Learn Different Features
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
Spectral Dynamics in Neural Network Training: Mathematical Foundations for Understanding Representational Development
Steering Evaluation-Aware Language Models to Act Like They Are Deployed
Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning
Stream: Scaling up Mechanistic Interpretability to Long Context in LLMs via Sparse Attention
SuperActivators: Only the Tail of the Distribution Contains Reliable Concept Signals
Superposition in Mixture of Experts
Symbolic Policy Distillation for Interpretable Reinforcement Learning
Symbolic vs. Continuous Features in Transformers: A Digital Communication System's Explanation
The Anatomy of Alignment: Decomposing Preference Optimization by Steering Sparse Features
The Dual Power of Interpretable Token Embeddings: Jailbreaking Attacks and Defenses for Diffusion Model Unlearning
The Geometry of Self-Verification in a Task-Specific Reasoning Model
The Impossibility of Inverse Permutation Learning in Transformer Models
Thinking Hard, Going Misaligned: Emergent Misalignment in LLMs
Thought Anchors: Which LLM Reasoning Steps Matter?
Thought Branches: Interpreting LLM Reasoning Requires Resampling
Three Desiderata for Faithfulness in Machine Learning Explanations: The Case for Causal Abstraction
Token Entanglement in Subliminal Learning
TopKLoRA
Toward a Theory of Generalizability in LLM Mechanistic Interpretability Research
Towards a Mechanistic Understanding of Robustness in Finetuned Reasoning Models
Towards Understanding Multimodal Fine-Tuning: A Case Study into Spatial Features
Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition
Training Reliable Activation Probes With a Handful of Positive Examples
Transformers Don’t Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and Implications for Mechanistic Interpretability
Trilemma of Truth in Large Language Models
Uncovering Object Localization Mechanisms in VLMs
Understanding sparse autoencoder scaling in the presence of feature manifolds
Universal Neurons in GPT-2: Emergence, Persistence, and Functional Impact
Unsupervised decoding of encoded reasoning using language model interpretability
Unveiling the Latent Directions of Reflection in Large Language Models
Vector Arithmetic in Concept and Token Subspaces
Visual Exploration of Feature Relationships in Sparse Autoencoders with Curated Concepts
WASP: A Weight-Space Approach to Detecting Learned Spuriousness
Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs
What Affects the Effective Depth of Large Language Models?
What Do Refusal Tokens Learn? Fine-Grained Representations and Evidence for Downstream Steering
When seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language Models
Where's the Bug? Attention Probing for Scalable Fault Localization
Who is In Charge? Dissecting Role Conflicts in LLM Instruction Following