{"total":96,"rows":[{"id":"2402.11004","title":"The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains","created":"2024-02-16","cited_by_count":118,"area":null},{"id":"2403.15371","title":"Can large language models explore in-context?","created":"2024-03-22","cited_by_count":76,"area":null},{"id":"2312.06528","title":"Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context","created":"2023-12-11","cited_by_count":63,"area":null},{"id":"2410.13835","title":"Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs","created":"2024-10-17","cited_by_count":56,"area":null},{"id":"2405.11751","title":"Asymptotic theory of in-context learning by linear attention","created":"2024-05-20","cited_by_count":55,"area":null},{"id":"2402.01258","title":"Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape","created":"2024-02-02","cited_by_count":46,"area":null},{"id":"2501.16265","title":"Training Dynamics of In-Context Learning in Linear Attention","created":"2025-01-27","cited_by_count":46,"area":null},{"id":"2405.19592","title":"Why Larger Language Models Do In-context Learning Differently?","created":"2024-05-30","cited_by_count":45,"area":null},{"id":"2405.18634","title":"A Theoretical Understanding of Self-Correction through In-context Alignment","created":"2024-05-28","cited_by_count":44,"area":"lr"},{"id":"2402.18819","title":"Dual Operating Modes of In-Context Learning","created":"2024-02-29","cited_by_count":43,"area":null},{"id":"2408.10147","title":"In-Context Learning with Representations: Contextual Generalization of Trained Transformers","created":"2024-08-19","cited_by_count":38,"area":null},{"id":"2408.12186","title":"Transformers are Minimax Optimal Nonparametric In-Context Learners","created":"2024-08-22","cited_by_count":37,"area":null},{"id":"2402.15607","title":"How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?","created":"2024-02-23","cited_by_count":35,"area":null},{"id":"2402.14951","title":"In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization","created":"2024-02-22","cited_by_count":33,"area":null},{"id":"2406.02128","title":"Iteration Head: A Mechanistic Study of Chain-of-Thought","created":"2024-06-04","cited_by_count":31,"area":"lr"},{"id":"2411.02544","title":"Pretrained transformer efficiently learns low-dimensional target functions in-context","created":"2024-11-04","cited_by_count":31,"area":null},{"id":"2408.14511","title":"Unveiling the Statistical Foundations of Chain-of-Thought Prompting Methods","created":"2024-08-25","cited_by_count":29,"area":"lr"},{"id":"2407.10005","title":"Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond","created":"2024-07-13","cited_by_count":24,"area":null},{"id":"2402.11639","title":"In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness","created":"2024-02-18","cited_by_count":22,"area":null},{"id":"2410.11268","title":"Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent","created":"2024-10-15","cited_by_count":22,"area":null},{"id":"2510.10981","title":"In-Context Learning Is Provably Bayesian Inference: A Generalization Theory for Meta-Learning","created":"2025-10-13","cited_by_count":22,"area":null},{"id":"2410.23042","title":"Toward Understanding In-context vs. In-weight Learning","created":"2024-10-30","cited_by_count":19,"area":null},{"id":"2401.17426","title":"Superiority of Multi-Head Attention in In-Context Linear Regression","created":"2024-01-30","cited_by_count":17,"area":null},{"id":"2406.11233","title":"Probing the Decision Boundaries of In-context Learning in Large Language Models","created":"2024-06-17","cited_by_count":17,"area":null},{"id":"2503.11842","title":"Test-Time Training Provably Improves Transformers as In-context Learners","created":"2025-03-14","cited_by_count":16,"area":null},{"id":"2510.01098","title":"Theory of Scaling Laws for In-Context Regression: Depth, Width, Context and Time","created":"2025-10-01","cited_by_count":16,"area":null},{"id":"2410.01774","title":"Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context","created":"2024-10-02","cited_by_count":15,"area":null},{"id":"2410.11778","title":"On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures","created":"2024-10-15","cited_by_count":15,"area":null},{"id":"2402.02212","title":"A Survey to Recent Progress Towards Understanding In-Context Learning","created":"2024-02-03","cited_by_count":14,"area":null},{"id":"2408.04532","title":"How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression","created":"2024-08-08","cited_by_count":14,"area":null},{"id":"2410.02167","title":"Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis","created":"2024-10-03","cited_by_count":14,"area":"lr"},{"id":"2410.05603","title":"Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition","created":"2024-10-08","cited_by_count":14,"area":"mechinterp"},{"id":"2502.04204","title":"Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence","created":"2025-02-06","cited_by_count":14,"area":"safety"},{"id":"2506.06489","title":"Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks","created":"2025-06-06","cited_by_count":14,"area":null},{"id":"2405.15618","title":"MLPs Learn In-Context on Regression and Classification Tasks","created":"2024-05-24","cited_by_count":13,"area":null},{"id":"2410.05629","title":"Vector-ICL: In-context Learning with Continuous Vector Representations","created":"2024-10-08","cited_by_count":13,"area":null},{"id":"2504.04308","title":"Gating is Weighting: Understanding Gated Linear Attention through In-context Learning","created":"2025-04-06","cited_by_count":12,"area":null},{"id":"2506.09048","title":"Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations","created":"2025-06-10","cited_by_count":9,"area":null},{"id":"2510.12066","title":"AI Agents as Universal Task Solvers","created":"2025-10-14","cited_by_count":9,"area":null},{"id":"2311.00226","title":"Transformers are Provably Optimal In-context Estimators for Wireless Communications","created":"2023-11-01","cited_by_count":8,"area":null},{"id":"2411.05189","title":"Understanding In-Context Learning of Linear Models in Transformers Through an Adversarial Lens","created":"2024-11-07","cited_by_count":8,"area":null},{"id":"2505.05145","title":"Understanding In-context Learning of Addition via Activation Subspaces","created":"2025-05-08","cited_by_count":8,"area":null},{"id":"2508.19999","title":"Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation","created":"2025-08-27","cited_by_count":8,"area":null},{"id":"2509.26551","title":"Pretrain-Test Task Alignment Governs Generalization in In-Context Learning","created":"2025-09-30","cited_by_count":8,"area":null},{"id":"2501.18187","title":"On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning","created":"2025-01-30","cited_by_count":7,"area":null},{"id":"2409.12293","title":"In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator Learning","created":"2024-09-18","cited_by_count":6,"area":null},{"id":"2410.12783","title":"Context-Scaling versus Task-Scaling in In-Context Learning","created":"2024-10-16","cited_by_count":6,"area":null},{"id":"2502.03503","title":"Analyzing limits for in-context learning","created":"2025-02-05","cited_by_count":6,"area":null},{"id":"2506.15329","title":"When and How Unlabeled Data Provably Improve In-Context Learning","created":"2025-06-18","cited_by_count":6,"area":null},{"id":"2510.14717","title":"Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling","created":"2025-10-16","cited_by_count":6,"area":null},{"id":"2405.16845","title":"On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability","created":"2024-05-27","cited_by_count":5,"area":null},{"id":"2411.11465","title":"Re-examining learning linear functions in context","created":"2024-11-18","cited_by_count":5,"area":null},{"id":"2502.08136","title":"In-Context Learning of Linear Dynamical Systems with Transformers: Approximation Bounds and Depth-Separation","created":"2025-02-12","cited_by_count":4,"area":null},{"id":"2502.10760","title":"Why is prompting hard? Understanding prompts on binary sequence predictors","created":"2025-02-15","cited_by_count":4,"area":null},{"id":"2502.15609","title":"On the Robustness of Transformers against Context Hijacking for Linear Classification","created":"2025-02-21","cited_by_count":4,"area":null},{"id":"2503.02102","title":"Provable Benefits of Task-Specific Prompts for In-context Learning","created":"2025-03-03","cited_by_count":4,"area":null},{"id":"2506.15535","title":"A Simplified Analysis of SGD for Linear Regression with Weight Averaging","created":"2025-06-18","cited_by_count":4,"area":null},{"id":"2510.10425","title":"Softmax $\\geq$ Linear: Transformers may learn to classify in-context by kernel gradient descent","created":"2025-10-12","cited_by_count":4,"area":null},{"id":"2604.12151","title":"Distinct mechanisms underlying in-context learning in transformers","created":"2026-04-14","cited_by_count":4,"area":null},{"id":"2403.08585","title":"Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems","created":"2024-03-13","cited_by_count":3,"area":null},{"id":"2406.00131","title":"From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When","created":"2024-05-31","cited_by_count":3,"area":null},{"id":"2407.09375","title":"HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context","created":"2024-07-12","cited_by_count":3,"area":null},{"id":"2502.17024","title":"Towards Auto-Regressive Next-Token Prediction: In-Context Learning Emerges from Generalization","created":"2025-02-24","cited_by_count":3,"area":null},{"id":"2505.19107","title":"Optimization-Inspired Few-Shot Adaptation for Large Language Models","created":"2025-05-25","cited_by_count":3,"area":null},{"id":"2508.07571","title":"Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression","created":"2025-08-11","cited_by_count":3,"area":null},{"id":"2509.15152","title":"Asymptotic Study of In-context Learning with Random Transformers through Equivalent Models","created":"2025-09-18","cited_by_count":3,"area":null},{"id":"2603.20969","title":"Understanding Contextual Recall in Transformers: How Finetuning Enables In-Context Reasoning over Pretraining Knowledge","created":"2026-03-21","cited_by_count":3,"area":"lr"},{"id":"2405.15115","title":"Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification","created":"2024-05-24","cited_by_count":2,"area":null},{"id":"2408.02288","title":"Spin glass model of in-context learning","created":"2024-08-05","cited_by_count":2,"area":null},{"id":"2510.00399","title":"How Can Mamba Learn In Context with Outliers and Generalize Provably?","created":"2025-10-01","cited_by_count":2,"area":"ssm"},{"id":"2602.04872","title":"Multi-layer Cross-attention is Provably Optimal for Multi-modal In-context Learning","created":"2026-02-04","cited_by_count":2,"area":null},{"id":"2410.09701","title":"Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models","created":"2024-10-13","cited_by_count":1,"area":null},{"id":"2410.11444","title":"A Theoretical Survey on Foundation Models","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2509.22764","title":"In-Context Learning can Perform Continual Learning Like Humans","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2510.04548","title":"Learning Linear Regression with Low-Rank Tasks in-Context","created":"2025-10-06","cited_by_count":1,"area":null},{"id":"2510.19797","title":"Transformers are almost optimal metalearners for linear classification","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2510.25753","title":"How Data Mixing Shapes In-Context Learning: Asymptotic Equivalence for Transformers with MLPs","created":"2025-10-29","cited_by_count":1,"area":null},{"id":"2511.01292","title":"Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions","created":"2025-11-03","cited_by_count":1,"area":null},{"id":"2602.01137","title":"Self-Generative Adversarial Fine-Tuning for Large Language Models","created":"2026-02-01","cited_by_count":1,"area":"alignment"},{"id":"2602.23197","title":"Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models","created":"2026-02-26","cited_by_count":1,"area":null},{"id":"2604.12817","title":"Understanding and Improving Continuous Adversarial Training for LLMs via In-context Learning Theory","created":"2026-04-14","cited_by_count":1,"area":"safety"},{"id":"2605.04995","title":"Adaptivity Under Realizability Constraints: Comparing In-Context and Agentic Learning","created":"2026-05-06","cited_by_count":1,"area":"agents"},{"id":"2605.21292","title":"Unbiased Gradients, Moving Stability Boundaries: Exact Mini-Batch Geometry in Linear Self-Attention","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2606.06814","title":"The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces","created":"2026-06-05","cited_by_count":1,"area":null},{"id":"2607.03660","title":"Sequential Correlations Change In-Context Learning: Effective Context Length and Architectural Mismatch","created":"2026-07-04","cited_by_count":1,"area":null},{"id":"2502.19787","title":"In-Context Learning with Hypothesis-Class Guidance","created":"2025-02-27","cited_by_count":0,"area":null},{"id":"2507.01414","title":"Decomposing Prediction Mechanisms for In-Context Recall","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2510.22594","title":"A Framework for Quantifying How Pre-Training and Context Benefit In-Context Learning","created":"2025-10-26","cited_by_count":0,"area":null},{"id":"2602.00576","title":"Data Distribution as a Lever for Guiding Optimizers Toward Superior Generalization in LLMs","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2603.13459","title":"Reconciling In-Context and In-Weight Learning via Dual Representation Space Encoding","created":"2026-03-13","cited_by_count":0,"area":null},{"id":"2603.22801","title":"Transformers Trained via Gradient Descent Can Provably Learn a Class of Teacher Models","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2605.28705","title":"Understanding Generalization and Forgetting in In-Context Continual Learning","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2605.30323","title":"In-Context Reward Adaptation for Robust Preference Modeling","created":"2026-05-28","cited_by_count":0,"area":"alignment"},{"id":"2607.04081","title":"A Unified Framework for In-Context Learning with Causal and Masked Language Models","created":"2026-07-05","cited_by_count":0,"area":null},{"id":"2609.32341","title":"A Comparative Analysis of Attention versus State-Space Models for In-Context Learning","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2610.17061","title":"In-context classification: Calibration and noise in linear attention with softmax readout","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}