{"total":77,"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":"2403.17806","title":"Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms","created":"2024-03-26","cited_by_count":149,"area":null},{"id":"2506.19823","title":"Persona Features Control Emergent Misalignment","created":"2025-06-24","cited_by_count":86,"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":"2407.10827","title":"LLM Circuit Analyses Are Consistent Across Training and Scale","created":"2024-07-15","cited_by_count":63,"area":null},{"id":"2406.16778","title":"Finding Transformer Circuits with Edge Pruning","created":"2024-06-24","cited_by_count":60,"area":null},{"id":"2505.14685","title":"Language Models use Lookbacks to Track Beliefs","created":"2025-05-20","cited_by_count":39,"area":null},{"id":"2507.16795","title":"Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning","created":"2025-07-22","cited_by_count":39,"area":null},{"id":"2407.15018","title":"Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions","created":"2024-07-21","cited_by_count":35,"area":null},{"id":"2503.02854","title":"(How) Do Language Models Track State?","created":"2025-03-04","cited_by_count":34,"area":null},{"id":"2504.02922","title":"Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning","created":"2025-04-03","cited_by_count":34,"area":null},{"id":"2505.16381","title":"PaTH Attention: Position Encoding via Accumulating Householder Transformations","created":"2025-05-22","cited_by_count":34,"area":null},{"id":"2405.21068","title":"Code Pretraining Improves Entity Tracking Abilities of Language Models","created":"2024-05-31","cited_by_count":31,"area":null},{"id":"2409.05448","title":"Representational Analysis of Binding in Language Models","created":"2024-09-09","cited_by_count":28,"area":null},{"id":"2510.13900","title":"Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences","created":"2025-10-14","cited_by_count":28,"area":null},{"id":"2510.06182","title":"Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context","created":"2025-10-07","cited_by_count":26,"area":null},{"id":"2412.01784","title":"Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models","created":"2024-12-02","cited_by_count":24,"area":null},{"id":"2412.03205","title":"U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs","created":"2024-12-04","cited_by_count":24,"area":null},{"id":"2407.14662","title":"Relational Composition in Neural Networks: A Survey and Call to Action","created":"2024-07-19","cited_by_count":23,"area":null},{"id":"2505.20896","title":"How Do Transformers Learn Variable Binding in Symbolic Programs?","created":"2025-05-27","cited_by_count":21,"area":null},{"id":"2502.11812","title":"Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis","created":"2025-02-17","cited_by_count":20,"area":null},{"id":"2410.01434","title":"Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models","created":"2024-10-02","cited_by_count":11,"area":null},{"id":"2503.11302","title":"Are formal and functional linguistic mechanisms dissociated in language models?","created":"2025-03-14","cited_by_count":11,"area":null},{"id":"2510.05092","title":"Learning to Interpret Weight Differences in Language Models","created":"2025-10-06","cited_by_count":11,"area":null},{"id":"2403.03942","title":"The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models","created":"2024-03-06","cited_by_count":10,"area":null},{"id":"2506.12044","title":"Why Do Some Inputs Break Low-Bit LLM Quantization?","created":"2025-05-24","cited_by_count":9,"area":null},{"id":"2410.05565","title":"Chain and Causal Attention for Efficient Entity Tracking","created":"2024-10-07","cited_by_count":8,"area":null},{"id":"2409.03274","title":"Recent Advances in Attack and Defense Approaches of Large Language Models","created":"2024-09-05","cited_by_count":6,"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":"2605.30233","title":"Do Language Models Track Entities Across State Changes?","created":"2026-05-28","cited_by_count":6,"area":null},{"id":"2507.07186","title":"Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs","created":"2025-07-09","cited_by_count":5,"area":null},{"id":"2512.16902","title":"In-Context Algebra","created":"2025-12-18","cited_by_count":5,"area":null},{"id":"2601.09445","title":"Where Knowledge Collides: A Mechanistic Study of Intra-Memory Knowledge Conflict in Language Models","created":"2026-01-14","cited_by_count":5,"area":null},{"id":"2604.19052","title":"Cell-Based Representation of Relational Binding in Language Models","created":"2026-04-21","cited_by_count":5,"area":null},{"id":"2410.22370","title":"Survey of User Interface Design and Interaction Techniques in Generative AI Applications","created":"2024-10-28","cited_by_count":4,"area":null},{"id":"2503.01896","title":"Neuroplasticity and Corruption in Model Mechanisms: A Case Study Of Indirect Object Identification","created":"2025-02-27","cited_by_count":3,"area":null},{"id":"2505.20076","title":"ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior","created":"2025-05-26","cited_by_count":3,"area":null},{"id":"2605.28860","title":"Mechanistic origins of catastrophic forgetting: why RL preserves circuits better than SFT?","created":"2026-05-21","cited_by_count":3,"area":null},{"id":"2608.13567","title":"Modular Cognitive Architecture Emerges in Large Language Models","created":"2026-06-27","cited_by_count":3,"area":null},{"id":"2412.17019","title":"Reversed Attention: On The Gradient Descent Of Attention Layers In GPT","created":"2024-12-22","cited_by_count":2,"area":null},{"id":"2507.09875","title":"Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2510.07452","title":"PATCH: Mitigating PII Leakage in Language Models with Privacy-Aware Targeted Circuit PatcHing","created":"2025-10-08","cited_by_count":2,"area":null},{"id":"2607.18921","title":"Circuit Claims Depend on What Is Extracted and How It Is Compared","created":"2026-07-21","cited_by_count":2,"area":null},{"id":"2407.10949","title":"Representing Rule-based Chatbots with Transformers","created":"2024-07-15","cited_by_count":1,"area":null},{"id":"2505.16178","title":"Understanding Fact Recall in Language Models: Why Two-Stage Training Encourages Memorization but Mixed Training Teaches Knowledge","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2505.17091","title":"Large Language Models Implicitly Learn to See and Hear Just By Reading","created":"2025-05-20","cited_by_count":1,"area":null},{"id":"2604.21139","title":"Slot Machines: How LLMs Keep Track of Multiple Entities","created":"2026-04-22","cited_by_count":1,"area":null},{"id":"2605.22476","title":"Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2610.05292","title":"Erased, Rerouted, or Rescaled? Post-Training and the Causal Quotient of a Language Model's Belief State","created":"2026-10-04","cited_by_count":1,"area":null},{"id":"2505.14892","title":"Scaling Laws for State Dynamics in Large Language Models","created":"2025-05-20","cited_by_count":0,"area":null},{"id":"2506.23423","title":"TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs","created":"2025-06-29","cited_by_count":0,"area":null},{"id":"2509.25002","title":"Circuit Distillation","created":"2025-09-29","cited_by_count":0,"area":null},{"id":"2604.00324","title":"The Persistent Vulnerability of Aligned AI Systems","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2605.07284","title":"Same Targets, Different Computation: How Post-Training Divides Work Across Model Layers","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.27969","title":"Boundary Suppression Asymmetry in Post-trained Assistants: Over-expansion as a Controllability Cost","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2606.01967","title":"Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.03085","title":"Multi-component Causal Tracing in Large Language Models","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.07555","title":"Persistent Priors, Preserved Targets: A Stroop-Style Paradigm for Lexical Override","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2606.16407","title":"A Mechanistic Understanding of Pronoun Fidelity in LLMs","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2607.08393","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","created":"2026-07-09","cited_by_count":0,"area":null},{"id":"2607.11945","title":"Belief-reality separation lives in routing over a shared value slot in language models","created":"2026-07-11","cited_by_count":0,"area":null},{"id":"2608.13626","title":"A Calibrated Test of Internal Action Maps: State Signals Without Global Affine Closure","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2608.17162","title":"OraclePhys: A Systematic Framework for LLM Fine-Tuning on Structural Mechanics","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2608.18083","title":"Entity tracking emerges in sub-billion parameter language models and exceeds human performance in naturalistic narratives","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2608.23969","title":"Investigating Knowledge Transfer Across Interactive Dialogue Games","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2608.26139","title":"Syntax vs. Semantics: How Transformers Learn Deep Dependencies","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2608.26462","title":"Diff Mining: Logit Differences Reveal Finetuning Objectives","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2609.21113","title":"Decoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models","created":"2026-09-17","cited_by_count":0,"area":null},{"id":"2609.29848","title":"Encoded but Not Decoded: Layer-Localized Evidence for a Three-Level Gap in LLM Syntax","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.33150","title":"Generalization Dynamics of LM Pre-training","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.33883","title":"Lost with a Map: Conversational State and Behavioral Reliability in Language Models","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.36221","title":"How Language Models Differ in Redistributing Attention-Head Activity Under Serial Demand","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.36585","title":"Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.38530","title":"Shifting Mechanisms: How Positional Encoding Choice Shapes In-Context Retrieval","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.15961","title":"Unfair and Unsafe: Everyday Bias Triggers Emergent Misalignment","created":"2026-10-11","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},{"id":"2610.19113","title":"From Copying to Composition: How Language Models Develop In-Context Learning","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}