{"total":101,"rows":[{"id":"2306.03341","title":"Inference-Time Intervention: Eliciting Truthful Answers from a Language Model","created":"2023-06-06","cited_by_count":1302,"area":null},{"id":"2212.04089","title":"Editing Models with Task Arithmetic","created":"2022-12-08","cited_by_count":1120,"area":null},{"id":"2406.15927","title":"Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs","created":"2024-06-22","cited_by_count":259,"area":null},{"id":"2404.03592","title":"ReFT: Representation Finetuning for Language Models","created":"2024-04-04","cited_by_count":197,"area":null},{"id":"2405.16833","title":"Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models","created":"2024-05-27","cited_by_count":125,"area":null},{"id":"2312.09230","title":"Successor Heads: Recurring, Interpretable Attention Heads In The Wild","created":"2023-12-14","cited_by_count":77,"area":null},{"id":"2404.01650","title":"Test-Time Model Adaptation with Only Forward Passes","created":"2024-04-02","cited_by_count":74,"area":null},{"id":"2505.22101","title":"MemOS: An Operating System for Memory-Augmented Generation (MAG) in Large Language Models","created":"2025-05-28","cited_by_count":73,"area":null},{"id":"2411.04986","title":"The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities","created":"2024-11-07","cited_by_count":69,"area":null},{"id":"2402.09631","title":"Representation Surgery: Theory and Practice of Affine Steering","created":"2024-02-15","cited_by_count":50,"area":null},{"id":"2507.16003","title":"Learning without training: The implicit dynamics of in-context learning","created":"2025-07-21","cited_by_count":43,"area":null},{"id":"2410.22685","title":"Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings","created":"2024-10-30","cited_by_count":30,"area":null},{"id":"2402.09236","title":"Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models","created":"2024-02-14","cited_by_count":29,"area":null},{"id":"2410.14516","title":"Do LLMs \"know\" internally when they follow instructions?","created":"2024-10-18","cited_by_count":26,"area":null},{"id":"2605.05115","title":"Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior","created":"2026-05-06","cited_by_count":26,"area":null},{"id":"2504.12459","title":"On Linear Representations and Pretraining Data Frequency in Language Models","created":"2025-04-16","cited_by_count":23,"area":null},{"id":"2310.08043","title":"Understanding and Controlling a Maze-Solving Policy Network","created":"2023-10-12","cited_by_count":22,"area":null},{"id":"2505.14827","title":"Text Generation Beyond Discrete Token Sampling","created":"2025-05-20","cited_by_count":21,"area":null},{"id":"2405.15454","title":"LiSeCo: Linear Semantic Control for Language Generation","created":"2024-05-24","cited_by_count":20,"area":null},{"id":"2511.05408","title":"Steering Language Models with Weight Arithmetic","created":"2025-11-07","cited_by_count":20,"area":null},{"id":"2404.09971","title":"Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs","created":"2024-04-15","cited_by_count":19,"area":null},{"id":"2406.04331","title":"PaCE: Parsimonious Concept Engineering for Large Language Models","created":"2024-06-06","cited_by_count":19,"area":null},{"id":"2510.22042","title":"Emotions Where Art Thou: Understanding and Characterizing the Emotional Latent Space of Large Language Models","created":"2025-10-24","cited_by_count":18,"area":null},{"id":"2502.00919","title":"Attention Sinks: A 'Catch, Tag, Release' Mechanism for Embeddings","created":"2025-02-02","cited_by_count":16,"area":null},{"id":"2406.03631","title":"Discovering Bias in Latent Space: An Unsupervised Debiasing Approach","created":"2024-06-05","cited_by_count":15,"area":null},{"id":"2602.02315","title":"The Shape of Beliefs: Geometry, Dynamics, and Interventions along Representation Manifolds of Language Models' Posteriors","created":"2026-02-02","cited_by_count":15,"area":null},{"id":"2412.10427","title":"Identifying and Manipulating Personality Traits in LLMs Through Activation Engineering","created":"2024-12-10","cited_by_count":14,"area":null},{"id":"2302.12480","title":"Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?","created":"2023-02-24","cited_by_count":13,"area":null},{"id":"2602.15669","title":"PERSONA: Dynamic and Compositional Inference-Time Personality Control via Activation Vector Algebra","created":"2026-02-17","cited_by_count":12,"area":null},{"id":"2405.14660","title":"Implicit In-context Learning","created":"2024-05-23","cited_by_count":11,"area":null},{"id":"2410.02899","title":"FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMs","created":"2024-10-03","cited_by_count":11,"area":null},{"id":"2502.05390","title":"Learning Task Representations from In-Context Learning","created":"2025-02-08","cited_by_count":11,"area":null},{"id":"2510.04013","title":"LLM Microscope: What Model Internals Reveal About Answer Correctness and Context Utilization","created":"2025-10-05","cited_by_count":11,"area":null},{"id":"2510.04491","title":"Impatient Users Confuse AI Agents: High-fidelity Simulations of Human Traits for Testing Agents","created":"2025-10-06","cited_by_count":10,"area":null},{"id":"2605.01148","title":"Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Concepts","created":"2026-05-01","cited_by_count":10,"area":null},{"id":"2406.11624","title":"Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers","created":"2024-06-17","cited_by_count":9,"area":null},{"id":"2409.06328","title":"Extracting Paragraphs from LLM Token Activations","created":"2024-09-10","cited_by_count":9,"area":null},{"id":"2404.05783","title":"A Survey on Responsible Generative AI: What to Generate and What Not","created":"2024-04-08","cited_by_count":8,"area":null},{"id":"2504.20500","title":"UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation","created":"2025-04-29","cited_by_count":8,"area":null},{"id":"2507.06445","title":"Can Interpretation Predict Behavior on Unseen Data?","created":"2025-07-08","cited_by_count":8,"area":null},{"id":"2602.00333","title":"Efficient and accurate steering of Large Language Models through attention-guided feature learning","created":"2026-01-30","cited_by_count":8,"area":null},{"id":"2603.01281","title":"Spectral Attention Steering for Prompt Highlighting","created":"2026-03-01","cited_by_count":8,"area":null},{"id":"2509.07983","title":"Steering Protein Language Models","created":"2025-07-01","cited_by_count":7,"area":null},{"id":"2512.15134","title":"From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?","created":"2025-12-17","cited_by_count":7,"area":null},{"id":"2502.04075","title":"From Rational Answers to Emotional Resonance: The Role of Controllable Emotion Generation in Language Models","created":"2025-02-06","cited_by_count":6,"area":null},{"id":"2602.10161","title":"Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamics Mechanisms and Efficient Alignment","created":"2026-02-10","cited_by_count":6,"area":null},{"id":"2410.22944","title":"Focus On This, Not That! Steering LLMs with Adaptive Feature Specification","created":"2024-10-30","cited_by_count":5,"area":null},{"id":"2502.06809","title":"Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution","created":"2025-02-04","cited_by_count":5,"area":null},{"id":"2404.07117","title":"Continuous Language Model Interpolation for Dynamic and Controllable Text Generation","created":"2024-04-10","cited_by_count":3,"area":null},{"id":"2502.16385","title":"Toward a Flexible Framework for Linear Representation Hypothesis Using Maximum Likelihood Estimation","created":"2025-02-22","cited_by_count":3,"area":null},{"id":"2502.17541","title":"Dataset Featurization: Uncovering Natural Language Features through Unsupervised Data Reconstruction","created":"2025-02-24","cited_by_count":3,"area":null},{"id":"2509.24169","title":"Task Vectors, Learned Not Extracted: Performance Gains and Mechanistic Insight","created":"2025-09-29","cited_by_count":3,"area":null},{"id":"2510.08734","title":"Transmuting prompts into weights","created":"2025-10-09","cited_by_count":3,"area":null},{"id":"2602.04903","title":"Mind the Performance Gap: Capability-Behavior Trade-offs in Feature Steering","created":"2026-02-03","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":"2210.12582","title":"Language Model Pre-Training with Sparse Latent Typing","created":"2022-10-23","cited_by_count":2,"area":null},{"id":"2507.05158","title":"Steering Information Utility in Key-Value Memory for Language Model Post-Training","created":"2025-07-07","cited_by_count":2,"area":null},{"id":"2510.12121","title":"Precise Attribute Intensity Control in Large Language Models via Targeted Representation Editing","created":"2025-10-14","cited_by_count":2,"area":null},{"id":"2602.06020","title":"Two Stages of Folding: Convergent Mechanisms in AI Protein Folding Trunks","created":"2026-02-05","cited_by_count":2,"area":null},{"id":"2603.10705","title":"PRISM-$\\Delta$: Differential Subspace Steering for Prompt Highlighting in Large Language Models","created":"2026-03-11","cited_by_count":2,"area":null},{"id":"2604.10027","title":"SinkTrack: Attention Sink based Context Anchoring for Large Language Models","created":"2026-04-11","cited_by_count":2,"area":null},{"id":"2606.05290","title":"Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation","created":"2026-06-03","cited_by_count":2,"area":null},{"id":"2607.20436","title":"Routing Subspaces: Auditing Evaluation-to-Deployment Mismatch in Fine-Tuned Language Models","created":"2026-05-11","cited_by_count":2,"area":null},{"id":"2505.08463","title":"RepCali: High Efficient Fine-tuning Via Representation Calibration in Latent Space for Pre-trained Language Models","created":"2025-05-13","cited_by_count":1,"area":null},{"id":"2510.17909","title":"Atomic Literary Styling: Mechanistic Manipulation of Prose Generation in Neural Language Models","created":"2025-10-19","cited_by_count":1,"area":null},{"id":"2601.13707","title":"Attention-space Contrastive Guidance for Efficient Hallucination Mitigation in LVLMs","created":"2026-01-20","cited_by_count":1,"area":null},{"id":"2602.04521","title":"$C$-$\\Delta\\Theta$: Circuit-Restricted Weight Arithmetic for Selective Refusal","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2602.08882","title":"Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2602.18671","title":"Spilled Energy in Large Language Models","created":"2026-02-21","cited_by_count":1,"area":null},{"id":"2605.01846","title":"Do Large Language Models Plan Answer Positions? Position Bias in Multiple-Choice Question Generation","created":"2026-05-03","cited_by_count":1,"area":null},{"id":"2605.09195","title":"The Geometry of Forgetting: Temporal Knowledge Drift as an Independent Axis in LLM Representations","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2605.09875","title":"Cross-Family Universality of Behavioral Axes via Anchor-Projected Representations","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2605.24942","title":"Riemannian-Manifold Steering: Geometry-Aware Generative Autoencoders for Label-Free Steering","created":"2026-05-24","cited_by_count":1,"area":null},{"id":"2606.05165","title":"STRIDE: Training Data Attribution via Sparse Recovery from Subset Perturbations","created":"2026-06-03","cited_by_count":1,"area":null},{"id":"2606.07822","title":"The ACUTE Protocol: Operationalizing Language Model Activations for Better Calibration, Utility, and Trust","created":"2026-06-05","cited_by_count":1,"area":null},{"id":"2607.11990","title":"Sparse Inter-Layer Dependencies of Transformer FFN Neurons","created":"2026-07-13","cited_by_count":1,"area":null},{"id":"2505.24292","title":"Mind the Quote: Enabling Quotation-Aware Dialogue in LLMs via Plug-and-Play Modules","created":"2025-05-30","cited_by_count":0,"area":null},{"id":"2602.01687","title":"Functional Subspace, where language models can use vector algebra to solve problems","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2604.04364","title":"Context is All You Need","created":"2026-04-06","cited_by_count":0,"area":null},{"id":"2604.07095","title":"Multilingual Embedding Probes Fail to Generalize Across Learner Corpora","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2604.17698","title":"The Geometric Canary: Predicting Steerability and Detecting Drift via Representational Stability","created":"2026-04-20","cited_by_count":0,"area":null},{"id":"2606.29503","title":"The Verbose Context Problem in Medical Records","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2607.03973","title":"MANCE: Manifold Aware Concept Erasure","created":"2026-07-04","cited_by_count":0,"area":null},{"id":"2607.16254","title":"More Than Memory: Task-Conditioned Signed FFN Writes in Long-Context Retrieval","created":"2026-06-27","cited_by_count":0,"area":null},{"id":"2608.06417","title":"Latent Fact-Checking: Detecting Misinformation through Activation Engineering","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2608.11822","title":"Located but Not Releasable: Silent Gate Inversion and Bounded Linear Release","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2608.16650","title":"PCA-guided Activation Scaling for Monotonic Bidirectional Control over LLM Sycophancy","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2608.20569","title":"Open-Weight Masked Introspection: Measuring What Language Models Can Report About Their Own Computation","created":"2026-08-20","cited_by_count":0,"area":null},{"id":"2609.01374","title":"Behaviorally Effective LoRA Writes Are Sparse and Structured","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.01551","title":"What, Where, and How: Probing Spatiotemporal Representations in Video Foundation Models","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.11253","title":"MUtE: A Dual Framework for Concept Erasure and Counterfactual Interventions","created":"2026-09-10","cited_by_count":0,"area":null},{"id":"2609.13072","title":"MAxBench: A Multinomial Concept Recovery Benchmark","created":"2026-09-11","cited_by_count":0,"area":null},{"id":"2609.30218","title":"Minimally Invasive Steering of Language Models","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.32449","title":"Self-Reports Do Not Identify Self-Models: An Identifiability Test for Counterfactual Reports","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.33722","title":"BOReFT: Manifold Steering of Language Models for Black-box Optimization","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.35970","title":"Causal and Interpretable Structures in LLM Compositional Tasks","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.38157","title":"EmoRES-TTS: Residual-Enhanced Vector Steering for Emotional Speech Generation","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.04183","title":"Language Model Activations Inhabit Privileged Error-Correcting Basins","created":"2026-10-03","cited_by_count":0,"area":null},{"id":"2610.06174","title":"Anosognosia in LLMs: Probing Self-Awareness of Quantized Computational Substrate","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.06897","title":"Capacity, Responsiveness and Alignment: What Makes a Latent Structure Actionable","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":"100"}