{"total":76,"rows":[{"id":"2503.18878","title":"I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders","created":"2025-03-24","cited_by_count":45,"area":"lr"},{"id":"2601.14004","title":"Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models","created":"2026-01-20","cited_by_count":27,"area":"mechinterp"},{"id":"2605.11887","title":"Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models","created":"2026-05-12","cited_by_count":21,"area":"mechinterp"},{"id":"2505.15634","title":"Feature Extraction and Steering for Enhanced Chain-of-Thought Reasoning in Language Models","created":"2025-05-21","cited_by_count":13,"area":"lr"},{"id":"2506.09227","title":"SoK: Machine Unlearning for Large Language Models","created":"2025-06-10","cited_by_count":11,"area":"safety"},{"id":"2506.19382","title":"Measuring and Guiding Monosemanticity","created":"2025-06-24","cited_by_count":10,"area":"mechinterp"},{"id":"2509.23799","title":"Enhancing LLM Steering through Sparse Autoencoder-Based Vector Refinement","created":"2025-09-28","cited_by_count":10,"area":"mechinterp"},{"id":"2509.22033","title":"OrtSAE: Orthogonal Sparse Autoencoders Uncover Atomic Features","created":"2025-09-26","cited_by_count":8,"area":"mechinterp"},{"id":"2511.06571","title":"Rep2Text: Decoding Full Text from a Single LLM Token Representation","created":"2025-11-09","cited_by_count":7,"area":null},{"id":"2512.08892","title":"Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders","created":"2025-12-09","cited_by_count":7,"area":"rag"},{"id":"2606.07612","title":"Position: Anthropomorphic Misalignment Research Needs Stronger Evidence","created":"2026-05-29","cited_by_count":7,"area":null},{"id":"2505.16170","title":"When Do LLMs Admit Their Mistakes? Understanding The Role Of Model Belief In Retraction","created":"2025-05-22","cited_by_count":6,"area":null},{"id":"2506.13060","title":"Rethinking Explainability in the Era of Multimodal AI","created":"2025-06-16","cited_by_count":6,"area":null},{"id":"2605.05980","title":"TACT: Mitigating Overthinking and Overacting in Coding Agents via Activation Steering","created":"2026-05-07","cited_by_count":6,"area":"lr"},{"id":"2605.18549","title":"Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics","created":"2026-05-18","cited_by_count":5,"area":"lr"},{"id":"2505.11611","title":"Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence","created":"2025-05-16","cited_by_count":4,"area":"mechinterp"},{"id":"2509.17665","title":"Mechanistic Interpretability with SAEs: Probing Religion, Violence, and Geography in Large Language Models","created":"2025-09-22","cited_by_count":4,"area":"mechinterp"},{"id":"2512.02004","title":"AlignSAE: Concept-Aligned Sparse Autoencoders","created":"2025-12-01","cited_by_count":4,"area":"mechinterp"},{"id":"2605.22658","title":"SegCompass: Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning Segmentation","created":"2026-05-21","cited_by_count":4,"area":"lr"},{"id":"2606.22357","title":"ORBIT: Training-Free Multi-Attribute Behavioral Steering via Orthogonal Subspace Rotation","created":"2026-06-21","cited_by_count":4,"area":"mechinterp"},{"id":"2509.23982","title":"Toward Preference-aligned Large Language Models via Residual-based Model Steering","created":"2025-09-28","cited_by_count":3,"area":"alignment"},{"id":"2512.05534","title":"A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima","created":"2025-12-05","cited_by_count":3,"area":"mechinterp"},{"id":"2601.03671","title":"NeuronScope: A Multi-Agent Framework for Explaining Polysemantic Neurons in Language Models","created":"2026-01-07","cited_by_count":3,"area":"agents"},{"id":"2602.00621","title":"Towards Interpretable Hallucination Analysis and Mitigation in LVLMs via Contrastive Neuron Steering","created":"2026-01-31","cited_by_count":3,"area":"mechinterp"},{"id":"2602.22719","title":"Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks","created":"2026-02-26","cited_by_count":3,"area":"ssm"},{"id":"2603.02578","title":"How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities","created":"2026-03-03","cited_by_count":3,"area":null},{"id":"2606.11657","title":"Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics","created":"2026-06-10","cited_by_count":3,"area":"mechinterp"},{"id":"2505.14420","title":"SAE-FiRE: Enhancing Earnings Surprise Predictions Through Sparse Autoencoder Feature Selection","created":"2025-05-20","cited_by_count":2,"area":"mechinterp"},{"id":"2505.19333","title":"Evaluating Steering Techniques using Human Similarity Judgments","created":"2025-05-25","cited_by_count":2,"area":null},{"id":"2602.17229","title":"Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy","created":"2026-02-19","cited_by_count":2,"area":"mechinterp"},{"id":"2605.17204","title":"Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies","created":"2026-05-17","cited_by_count":2,"area":"vla"},{"id":"2606.04284","title":"Sparse Mixture-of-Experts Reward Models Learn Interpretable and Specialized Experts for Personalized Preference Modeling","created":"2026-06-02","cited_by_count":2,"area":"alignment"},{"id":"2606.06188","title":"The Tell-Tale Norm: $\\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models","created":"2026-06-04","cited_by_count":2,"area":"lr"},{"id":"2606.24716","title":"Evaluating the Interpretability of Sparse Autoencoders with Concept Annotations","created":"2026-06-23","cited_by_count":2,"area":"mllm"},{"id":"2505.11576","title":"Concept-Guided Interpretability via Neural Chunking","created":"2025-05-16","cited_by_count":1,"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":"2509.20376","title":"ConceptViz: A Visual Analytics Approach for Exploring Concepts in Large Language Models","created":"2025-09-20","cited_by_count":1,"area":"mechinterp"},{"id":"2509.20997","title":"Binary Autoencoder for Mechanistic Interpretability of Large Language Models","created":"2025-09-25","cited_by_count":1,"area":"mechinterp"},{"id":"2510.11235","title":"AI Alignment Strategies from a Risk Perspective: Independent Safety Mechanisms or Shared Failures?","created":"2025-10-13","cited_by_count":1,"area":null},{"id":"2511.00029","title":"Feature-Guided SAE Steering for Refusal-Rate Control using Contrasting Prompts","created":"2025-10-26","cited_by_count":1,"area":"mechinterp"},{"id":"2511.05745","title":"Beyond Redundancy: Diverse and Specialized Multi-Expert Sparse Autoencoder","created":"2025-11-07","cited_by_count":1,"area":"moe"},{"id":"2605.17659","title":"Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes","created":"2026-05-17","cited_by_count":1,"area":null},{"id":"2605.28553","title":"Refusal Before Decoding: Detecting and Exploiting Refusal Signals in Intermediate LLM Activations","created":"2026-05-27","cited_by_count":1,"area":"mechinterp"},{"id":"2606.22994","title":"Do Sparse Autoencoders Learn Meaningful Concept Hierarchies?","created":"2026-06-22","cited_by_count":1,"area":"mechinterp"},{"id":"2606.24997","title":"What's in an Earth Embedding? An Explainability Analysis of Location Encoders","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2607.07316","title":"Mechanistic Interpretability for Neural Networks: Circuits, Sparse Features and Symbolic Reasoning","created":"2026-07-08","cited_by_count":1,"area":"lr"},{"id":"2607.24645","title":"Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects","created":"2026-07-27","cited_by_count":1,"area":"mechinterp"},{"id":"2505.22506","title":"Sparsification and Reconstruction from the Perspective of Representation Geometry","created":"2025-05-28","cited_by_count":0,"area":"mechinterp"},{"id":"2506.21468","title":"TopK Language Models","created":"2025-06-26","cited_by_count":0,"area":"mechinterp"},{"id":"2508.14275","title":"Disentangling concept semantics via multilingual averaging in Sparse Autoencoders","created":"2025-08-19","cited_by_count":0,"area":"mechinterp"},{"id":"2509.15667","title":"VOX-KRIKRI: Unifying Speech and Language through Continuous Fusion","created":"2025-09-19","cited_by_count":0,"area":null},{"id":"2509.22015","title":"Concept-SAE: A Controllable and Invertible Concept Interface for Sparse Autoencoders","created":"2025-09-26","cited_by_count":0,"area":"mechinterp"},{"id":"2510.16565","title":"Language over Content: Tracing Cultural Understanding in Multilingual Large Language Models","created":"2025-10-18","cited_by_count":0,"area":null},{"id":"2511.12723","title":"LAYA: Layer-wise Attention Aggregation for Interpretable Depth-Aware Neural Networks","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2511.19264","title":"Interpreting GFlowNets for Drug Discovery: What probes can and cannot show","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2512.20638","title":"Uncovering Competency Gaps in Large Language Models and Their Benchmarks","created":"2025-12-06","cited_by_count":0,"area":null},{"id":"2601.11691","title":"Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype","created":"2026-01-16","cited_by_count":0,"area":null},{"id":"2602.19115","title":"How Do LLMs Encode Scientific Quality? An Empirical Study Using Monosemantic Features from Sparse Autoencoders","created":"2026-02-22","cited_by_count":0,"area":"mechinterp"},{"id":"2603.05925","title":"RAC: Rectified Flow Auto Coder","created":"2026-03-06","cited_by_count":0,"area":"diffusion"},{"id":"2604.23877","title":"Knowledge Vector of Logical Reasoning in Large Language Models","created":"2026-04-26","cited_by_count":0,"area":"lr"},{"id":"2605.06494","title":"From Token Lists to Graph Motifs: Weisfeiler-Lehman Analysis of Sparse Autoencoder Features","created":"2026-05-07","cited_by_count":0,"area":"mechinterp"},{"id":"2605.22532","title":"Relational Linear Properties in Language Models: An Empirical Investigation","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2607.04593","title":"TORINO: Token Reduction via Interpretable Concept Overlap in Vision-Language Models","created":"2026-07-06","cited_by_count":0,"area":"mllm"},{"id":"2607.08499","title":"Cross-seed explainability using Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders","created":"2026-07-09","cited_by_count":0,"area":"mechinterp"},{"id":"2607.21620","title":"From Profiles to Steering Vectors: Global Sparse Priors and Local Semantic Calibration for Personalized Text Generation","created":"2026-06-01","cited_by_count":0,"area":"mechinterp"},{"id":"2607.24484","title":"What do Reward Models Memorize?","created":"2026-07-27","cited_by_count":0,"area":"alignment"},{"id":"2608.15042","title":"Uncovering Hidden Leptonic Correlations with Flow Matching and Autoencoders","created":"2026-08-15","cited_by_count":0,"area":null},{"id":"2608.24758","title":"RACE: Scalable Statistical Estimation of Functional Consistency in LLM Neurons","created":"2026-08-25","cited_by_count":0,"area":"mechinterp"},{"id":"2608.25941","title":"When Pruning Meets Interpretability: Preserving Sparse Autoencoder Robustness in LLMs","created":"2026-08-26","cited_by_count":0,"area":"mechinterp"},{"id":"2609.28809","title":"Stream Recursion Model (SRM)","created":"2026-09-23","cited_by_count":0,"area":"mechinterp"},{"id":"2609.33183","title":"Identifying Temporal Features within Transcoders for Time Sensitive Factual Recall","created":"2026-09-27","cited_by_count":0,"area":"mechinterp"},{"id":"2609.38205","title":"The System Prompt Illusion: How Instruction Preambles Modify Computation in Language Models","created":"2026-09-23","cited_by_count":0,"area":null},{"id":"2610.00848","title":"Geometric Similarity in VLM Low-Level Vision Representations","created":"2026-10-01","cited_by_count":0,"area":"mllm"},{"id":"2610.01177","title":"Temporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models","created":"2026-10-01","cited_by_count":0,"area":"diffusion"},{"id":"2610.04283","title":"First-Order Steering: Translating Weight Adaptation into Activation Steering","created":"2026-10-03","cited_by_count":0,"area":"mechinterp"},{"id":"2610.20139","title":"Sparse Autoencoders for Mechanistic Interpretability in NLP: A Critical Survey of Recoverability, Interpretability, and Utility","created":"2026-10-14","cited_by_count":0,"area":"mechinterp"}],"next_cursor":null}