{"total":110,"rows":[{"id":"2403.19647","title":"Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models","created":"2024-03-28","cited_by_count":435,"area":null},{"id":"2404.14082","title":"Mechanistic Interpretability for AI Safety -- A Review","created":"2024-04-22","cited_by_count":422,"area":"mechinterp"},{"id":"2309.16042","title":"Towards Best Practices of Activation Patching in Language Models: Metrics and Methods","created":"2023-09-27","cited_by_count":359,"area":"mechinterp"},{"id":"2306.03819","title":"LEACE: Perfect linear concept erasure in closed form","created":"2023-06-06","cited_by_count":267,"area":null},{"id":"2307.02477","title":"Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks","created":"2023-07-05","cited_by_count":246,"area":"lr"},{"id":"2501.17148","title":"AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders","created":"2025-01-28","cited_by_count":218,"area":"mechinterp"},{"id":"2404.15255","title":"How to use and interpret activation patching","created":"2024-04-23","cited_by_count":214,"area":null},{"id":"2303.02536","title":"Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations","created":"2023-03-05","cited_by_count":209,"area":null},{"id":"2301.04709","title":"Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability","created":"2023-01-11","cited_by_count":205,"area":"mechinterp"},{"id":"2404.03592","title":"ReFT: Representation Finetuning for Language Models","created":"2024-04-04","cited_by_count":197,"area":null},{"id":"2304.05969","title":"Localizing Model Behavior with Path Patching","created":"2023-04-12","cited_by_count":195,"area":null},{"id":"2307.15771","title":"The Hydra Effect: Emergent Self-repair in Language Model Computations","created":"2023-07-28","cited_by_count":156,"area":null},{"id":"2209.11326","title":"Towards Faithful Model Explanation in NLP: A Survey","created":"2022-09-22","cited_by_count":130,"area":null},{"id":"2207.13243","title":"Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks","created":"2022-07-27","cited_by_count":129,"area":null},{"id":"2403.00745","title":"AtP*: An efficient and scalable method for localizing LLM behaviour to components","created":"2024-03-01","cited_by_count":111,"area":"mechinterp"},{"id":"2305.08809","title":"Interpretability at Scale: Identifying Causal Mechanisms in Alpaca","created":"2023-05-15","cited_by_count":103,"area":null},{"id":"2405.00208","title":"A Primer on the Inner Workings of Transformer-based Language Models","created":"2024-04-30","cited_by_count":85,"area":null},{"id":"2403.07809","title":"pyvene: A Library for Understanding and Improving PyTorch Models via Interventions","created":"2024-03-12","cited_by_count":54,"area":null},{"id":"2407.15017","title":"Knowledge Mechanisms in Large Language Models: A Survey and Perspective","created":"2024-07-22","cited_by_count":51,"area":null},{"id":"2402.12560","title":"CausalGym: Benchmarking causal interpretability methods on linguistic tasks","created":"2024-02-19","cited_by_count":46,"area":null},{"id":"2309.10312","title":"Rigorously Assessing Natural Language Explanations of Neurons","created":"2023-09-19","cited_by_count":45,"area":null},{"id":"2402.07321","title":"Summing Up the Facts: Additive Mechanisms Behind Factual Recall in LLMs","created":"2024-02-11","cited_by_count":42,"area":null},{"id":"2505.14685","title":"Language Models use Lookbacks to Track Beliefs","created":"2025-05-20","cited_by_count":39,"area":null},{"id":"2404.03646","title":"Locating and Editing Factual Associations in Mamba","created":"2024-04-04","cited_by_count":37,"area":"ssm"},{"id":"2507.08802","title":"The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability?","created":"2025-07-11","cited_by_count":37,"area":"mechinterp"},{"id":"2307.03637","title":"Discovering Variable Binding Circuitry with Desiderata","created":"2023-07-07","cited_by_count":34,"area":null},{"id":"2410.04332","title":"Gradient Routing: Masking Gradients to Localize Computation in Neural Networks","created":"2024-10-06","cited_by_count":34,"area":null},{"id":"2502.20914","title":"Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?","created":"2025-02-28","cited_by_count":34,"area":"mechinterp"},{"id":"2307.16851","title":"Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives","created":"2023-07-31","cited_by_count":30,"area":"alignment"},{"id":"2209.14279","title":"Causal Proxy Models for Concept-Based Model Explanations","created":"2022-09-28","cited_by_count":29,"area":null},{"id":"2309.05973","title":"Circuit Breaking: Removing Model Behaviors with Targeted Ablation","created":"2023-09-12","cited_by_count":27,"area":null},{"id":"2407.14494","title":"InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques","created":"2024-07-19","cited_by_count":25,"area":"mechinterp"},{"id":"2407.19200","title":"On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs","created":"2024-07-27","cited_by_count":25,"area":"mechinterp"},{"id":"2312.02073","title":"A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia","created":"2023-12-04","cited_by_count":24,"area":null},{"id":"2302.12461","title":"Analyzing And Editing Inner Mechanisms Of Backdoored Language Models","created":"2023-02-24","cited_by_count":23,"area":"safety"},{"id":"2112.02505","title":"Causal Distillation for Language Models","created":"2021-12-05","cited_by_count":19,"area":null},{"id":"2412.01953","title":"The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications","created":"2024-12-02","cited_by_count":18,"area":null},{"id":"2401.12631","title":"A Reply to Makelov et al. (2023)'s \"Interpretability Illusion\" Arguments","created":"2024-01-23","cited_by_count":17,"area":null},{"id":"2212.09897","title":"Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training","created":"2022-12-19","cited_by_count":16,"area":null},{"id":"2406.18400","title":"Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers","created":"2024-06-26","cited_by_count":15,"area":null},{"id":"2508.21258","title":"RelP: Faithful and Efficient Circuit Discovery in Language Models via Relevance Patching","created":"2025-08-28","cited_by_count":13,"area":"mechinterp"},{"id":"2512.18792","title":"The Dead Salmons of AI Interpretability","created":"2025-12-21","cited_by_count":12,"area":null},{"id":"2404.04332","title":"Scope Ambiguities in Large Language Models","created":"2024-04-05","cited_by_count":11,"area":null},{"id":"2506.15538","title":"Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework","created":"2025-06-18","cited_by_count":10,"area":null},{"id":"2407.09378","title":"Graph Neural Network Causal Explanation via Neural Causal Models","created":"2024-07-12","cited_by_count":9,"area":null},{"id":"2602.16698","title":"Causality is Key for Interpretability Claims to Generalise","created":"2026-02-18","cited_by_count":8,"area":null},{"id":"2305.12544","title":"Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models","created":"2023-05-21","cited_by_count":7,"area":null},{"id":"2506.16678","title":"Mechanisms vs. Outcomes: Probing for Syntax Fails to Explain Performance on Targeted Syntactic Evaluations","created":"2025-06-20","cited_by_count":7,"area":null},{"id":"2205.09787","title":"Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices)","created":"2022-05-19","cited_by_count":6,"area":null},{"id":"2211.07950","title":"Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs","created":"2022-11-15","cited_by_count":6,"area":null},{"id":"2211.09937","title":"Explainability Via Causal Self-Talk","created":"2022-11-17","cited_by_count":6,"area":null},{"id":"2302.00293","title":"A Survey of Methods, Challenges and Perspectives in Causality","created":"2023-02-01","cited_by_count":6,"area":null},{"id":"2409.13733","title":"RNR: Teaching Large Language Models to Follow Roles and Rules","created":"2024-09-10","cited_by_count":6,"area":null},{"id":"2501.19335","title":"What is causal about causal models and representations?","created":"2025-01-31","cited_by_count":6,"area":null},{"id":"2506.18852","title":"Mechanistic Interpretability Needs Philosophy","created":"2025-06-23","cited_by_count":6,"area":"mechinterp"},{"id":"2307.00660","title":"Minimum Levels of Interpretability for Artificial Moral Agents","created":"2023-07-02","cited_by_count":5,"area":null},{"id":"2401.08534","title":"DiConStruct: Causal Concept-based Explanations through Black-Box Distillation","created":"2024-01-16","cited_by_count":5,"area":"distill"},{"id":"2507.07544","title":"Position: We Need An Algorithmic Understanding of Generative AI","created":"2025-07-10","cited_by_count":5,"area":null},{"id":"2508.14067","title":"Punctuation and Predicates in Language Models","created":"2025-08-11","cited_by_count":5,"area":null},{"id":"2510.10161","title":"Large Language Model Sourcing: A Survey","created":"2025-10-11","cited_by_count":5,"area":null},{"id":"2303.00333","title":"Competence-Based Analysis of Language Models","created":"2023-03-01","cited_by_count":4,"area":null},{"id":"2402.11355","title":"A Practical Method for Generating String Counterfactuals","created":"2024-02-17","cited_by_count":4,"area":null},{"id":"2404.18988","title":"Markovian Transformers for Informative Language Modeling","created":"2024-04-29","cited_by_count":4,"area":"lr"},{"id":"2407.13594","title":"Validating Mechanistic Interpretations: An Axiomatic Approach","created":"2024-07-18","cited_by_count":4,"area":"mechinterp"},{"id":"2506.17052","title":"From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers","created":"2025-06-20","cited_by_count":4,"area":null},{"id":"2603.22278","title":"The Dual Mechanisms of Spatial Variable Binding in Vision-Language Models","created":"2026-03-23","cited_by_count":4,"area":"mllm"},{"id":"2607.08349","title":"Certified Interventional Fidelity: Anytime-Valid, Adaptive Evaluation of Causal Claims in Mechanistic Interpretability","created":"2026-07-09","cited_by_count":4,"area":"mechinterp"},{"id":"2305.08572","title":"Estimating the Causal Effects of Natural Logic Features in Neural NLI Models","created":"2023-05-15","cited_by_count":3,"area":null},{"id":"2312.05361","title":"Emergence and Function of Abstract Representations in Self-Supervised Transformers","created":"2023-12-08","cited_by_count":3,"area":"wm"},{"id":"2501.06164","title":"Model Alignment Search","created":"2025-01-10","cited_by_count":3,"area":"alignment"},{"id":"2511.21974","title":"Start Making Sense(s): A Developmental Probe of Attention Specialization Using Lexical Ambiguity","created":"2025-11-26","cited_by_count":3,"area":null},{"id":"2608.14894","title":"Can Neural Networks Learn by Experimenting on Themselves? Self-Interventional Learning from Functional Consequences to Predictive Self-Knowledge","created":"2026-08-14","cited_by_count":2,"area":null},{"id":"2608.15156","title":"Low-Rank Dynamics-Effective Latent Carriers for Counterfactual Rollout in Learned World Models","created":"2026-08-15","cited_by_count":2,"area":"wm"},{"id":"2406.08709","title":"Introducing Diminutive Causal Structure into Graph Representation Learning","created":"2024-06-13","cited_by_count":1,"area":null},{"id":"2410.09349","title":"Inference and Verbalization Functions During In-Context Learning","created":"2024-10-12","cited_by_count":1,"area":null},{"id":"2411.07071","title":"Universal Response and Emergence of Induction in LLMs","created":"2024-11-11","cited_by_count":1,"area":null},{"id":"2506.18887","title":"Steering Conceptual Bias via Transformer Latent-Subspace Activation","created":"2025-06-23","cited_by_count":1,"area":"mechinterp"},{"id":"2602.24266","title":"Causal Mechanism Reduction: Mechanism Replacement for Neural Network Pruning and Abstraction","created":"2026-02-27","cited_by_count":1,"area":null},{"id":"2605.22488","title":"Represented Is Not Computed: A Causal Test of Candidate Algorithmic Intermediates in a Transformer","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2606.24026","title":"Can Language Model Agents be Helpful Circuit Explainers in Mechanistic Interpretability?","created":"2026-06-23","cited_by_count":1,"area":"agents"},{"id":"2607.12985","title":"Resist and Update: Counterfactual Report Coordinates for Incentive-Compatible LLMs","created":"2026-07-14","cited_by_count":1,"area":"alignment"},{"id":"2205.07862","title":"A Safety Assurable Human-Inspired Perception Architecture","created":"2022-05-10","cited_by_count":0,"area":null},{"id":"2210.01266","title":"Interpretable Deep Tracking","created":"2022-10-03","cited_by_count":0,"area":null},{"id":"2211.08243","title":"Neural Bayesian Network Understudy","created":"2022-11-15","cited_by_count":0,"area":null},{"id":"2301.08496","title":"Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective","created":"2023-01-20","cited_by_count":0,"area":null},{"id":"2311.10905","title":"Flexible Model Interpretability through Natural Language Model Editing","created":"2023-11-17","cited_by_count":0,"area":null},{"id":"2410.05484","title":"Neural Networks Decoded: Targeted and Robust Analysis of Neural Network Decisions via Causal Explanations and Reasoning","created":"2024-10-07","cited_by_count":0,"area":null},{"id":"2503.14442","title":"Inducing Causal Structure for Interpretable Neural Networks Applied to Glucose Prediction for T1DM Patients","created":"2025-03-18","cited_by_count":0,"area":null},{"id":"2505.06320","title":"Divide (Text) and Conquer (Sentiment): Improved Sentiment Classification by Constituent Conflict Resolution","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2507.11768","title":"LLMs are Bayesian, In Expectation, Not in Realization","created":"2025-07-15","cited_by_count":0,"area":null},{"id":"2601.11618","title":"Architecture Before the Formula: Training-Dependent Computational Semantics in Transformers","created":"2026-01-10","cited_by_count":0,"area":null},{"id":"2603.03359","title":"ACES: Accent Subspaces for Coupling, Explanations, and Stress-Testing in Automatic Speech Recognition","created":"2026-02-28","cited_by_count":0,"area":null},{"id":"2603.18029","title":"Engineering Verifiable Modularity in Transformers via Per-Layer Supervision","created":"2026-03-08","cited_by_count":0,"area":null},{"id":"2603.27070","title":"Structural Graph Probing of Vision-Language Models","created":"2026-03-28","cited_by_count":0,"area":"mllm"},{"id":"2605.06979","title":"PLOT: Progressive Localization via Optimal Transport in Neural Causal Abstraction","created":"2026-05-07","cited_by_count":0,"area":"mechinterp"},{"id":"2605.25156","title":"Abduction-Deduction Entanglement: Domain Generalization via Representation Transplants","created":"2026-05-24","cited_by_count":0,"area":null},{"id":"2607.00267","title":"Validating Causal Abstraction Metrics on Simulated Complex Systems","created":"2026-06-30","cited_by_count":0,"area":null},{"id":"2607.24471","title":"Grounding latent algorithm routing in transformer reasoning","created":"2026-07-27","cited_by_count":0,"area":"lr"},{"id":"2607.26192","title":"Dynamic Parameterization Is Not Dynamic Inference","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2608.07214","title":"Toward a Causal Data Management Ecosystem for Decision Making and Agentic AI","created":"2026-08-07","cited_by_count":0,"area":"agents"}],"next_cursor":"100"}