{"total":32,"rows":[{"id":"2501.08319","title":"Enhancing Automated Interpretability with Output-Centric Feature Descriptions","created":"2025-01-14","cited_by_count":41,"area":null},{"id":"2511.08579","title":"Training Language Models to Explain Their Own Computations","created":"2025-11-11","cited_by_count":30,"area":null},{"id":"2505.20322","title":"Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms","created":"2025-05-23","cited_by_count":24,"area":null},{"id":"2512.15712","title":"Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants","created":"2025-12-17","cited_by_count":12,"area":null},{"id":"2602.02464","title":"From Directions to Regions: Decomposing Activations in Language Models via Local Geometry","created":"2026-02-02","cited_by_count":12,"area":null},{"id":"2504.07440","title":"Model Utility Law: Evaluating LLMs beyond Performance through Mechanism Interpretable Metric","created":"2025-04-10","cited_by_count":11,"area":null},{"id":"2505.22586","title":"Precise In-Parameter Concept Erasure in Large Language Models","created":"2025-05-28","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":"2501.04835","title":"Do Code LLMs Understand Design Patterns?","created":"2025-01-08","cited_by_count":9,"area":null},{"id":"2507.14240","title":"HuggingGraph: Understanding the Supply Chain of LLM Ecosystem","created":"2025-07-17","cited_by_count":8,"area":null},{"id":"2509.17196","title":"Evolution of Concepts in Language Model Pre-Training","created":"2025-09-21","cited_by_count":8,"area":null},{"id":"2506.13978","title":"AI shares emotion with humans across languages and cultures","created":"2025-06-11","cited_by_count":6,"area":null},{"id":"2602.05735","title":"CSRv2: Unlocking Ultra-Sparse Embeddings","created":"2026-02-05","cited_by_count":6,"area":null},{"id":"2505.16505","title":"Sparse Activation Editing for Reliable Instruction Following in Narratives","created":"2025-05-22","cited_by_count":4,"area":null},{"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":"2510.01228","title":"Who is In Charge? Dissecting Role Conflicts in Instruction Following","created":"2025-09-23","cited_by_count":3,"area":null},{"id":"2606.29604","title":"Mechanistically Eliciting Latent Behaviors in Language Models","created":"2026-06-28","cited_by_count":3,"area":null},{"id":"2608.12036","title":"Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence","created":"2026-08-12","cited_by_count":2,"area":null},{"id":"2508.19414","title":"Even Heads Fix Odd Errors: Mechanistic Discovery and Surgical Repair in Transformer Attention","created":"2025-08-26","cited_by_count":1,"area":null},{"id":"2509.24815","title":"Efficient Sketching and Nearest Neighbor Search Algorithms for Sparse Vector Sets","created":"2025-09-29","cited_by_count":1,"area":null},{"id":"2604.11297","title":"The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping","created":"2026-04-13","cited_by_count":1,"area":null},{"id":"2605.02234","title":"Bucketing the Good Apples: A Method for Diagnosing and Improving Causal Abstraction","created":"2026-05-04","cited_by_count":1,"area":null},{"id":"2606.08267","title":"Post-AGI Economies: Superposition and the Second Fundamental Theorem of Welfare Economics","created":"2026-06-06","cited_by_count":1,"area":null},{"id":"2609.25518","title":"Matryoshka attribution: Learning to attribute language model outputs to representations and weights","created":"2026-09-22","cited_by_count":1,"area":null},{"id":"2506.15735","title":"ContextBench: Modifying Contexts for Targeted Latent Activation","created":"2025-06-15","cited_by_count":0,"area":null},{"id":"2607.00397","title":"NeuroCogMap Reveals Cognitive Organization of Large Language Models","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2607.26853","title":"From Representations to Behaviors: Exploring the Person-Situation-Behavior Triad in LLMs","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2609.02089","title":"IDEEA: training-free Input-Dependent stEEring via Activation cluster matching","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.38718","title":"MetaSteer: Context-Conditioned, nonlinear Steering via Attention-Projection Adaptation","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.07791","title":"Illusory Pattern Perception Drives Spurious Inference in Large Language Models","created":"2026-10-06","cited_by_count":0,"area":null},{"id":"2610.12989","title":"Language Models Have Interpretable Narrative Mechanisms","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.17093","title":"SFT Leaves a Reproducible Signature in Activation Geometry: Calibrating Post-Training Interpretability Against Run-to-Run Noise","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}