{"total":54,"rows":[{"id":"2501.00070","title":"ICLR: In-Context Learning of Representations","created":"2024-12-29","cited_by_count":50,"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":"2503.21676","title":"How do language models learn facts? Dynamics, curricula and hallucinations","created":"2025-03-27","cited_by_count":37,"area":null},{"id":"2412.03782","title":"The broader spectrum of in-context learning","created":"2024-12-05","cited_by_count":35,"area":null},{"id":"2505.17127","title":"Pixels Versus Priors: Controlling Knowledge Priors in Vision-Language Models through Visual Counterfacts","created":"2025-05-21","cited_by_count":32,"area":"mllm"},{"id":"2511.00617","title":"Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering","created":"2025-11-01","cited_by_count":29,"area":"mechinterp"},{"id":"2505.17863","title":"The emergence of sparse attention: impact of data distribution and benefits of repetition","created":"2025-05-23","cited_by_count":25,"area":null},{"id":"2503.05631","title":"Strategy Coopetition Explains the Emergence and Transience of In-Context Learning","created":"2025-03-07","cited_by_count":17,"area":null},{"id":"2501.17745","title":"Dynamics of Transient Structure in In-Context Linear Regression Transformers","created":"2025-01-29","cited_by_count":14,"area":null},{"id":"2505.12075","title":"Do different prompting methods yield a common task representation in language models?","created":"2025-05-17","cited_by_count":11,"area":null},{"id":"2412.04619","title":"Sometimes I am a Tree: Data Drives Unstable Hierarchical Generalization","created":"2024-12-05","cited_by_count":10,"area":null},{"id":"2505.16694","title":"Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence","created":"2025-05-22","cited_by_count":10,"area":null},{"id":"2505.22756","title":"Decomposing Elements of Problem Solving: What \"Math\" Does RL Teach?","created":"2025-05-28","cited_by_count":10,"area":"lr"},{"id":"2605.29548","title":"Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention","created":"2026-05-28","cited_by_count":10,"area":null},{"id":"2601.22364","title":"Context Structure Reshapes the Representational Geometry of Language Models","created":"2026-01-29","cited_by_count":8,"area":null},{"id":"2510.00184","title":"Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls","created":"2025-09-30","cited_by_count":7,"area":null},{"id":"2511.16893","title":"Predicting the Emergence of Induction Heads in Language Model Pretraining","created":"2025-11-21","cited_by_count":7,"area":null},{"id":"2603.24676","title":"When Is Collective Intelligence a Lottery? Multi-Agent Scaling Laws for Memetic Drift in LLMs","created":"2026-03-25","cited_by_count":6,"area":"agents"},{"id":"2506.13253","title":"Distinct Computations Emerge From Compositional Curricula in In-Context Learning","created":"2025-06-16","cited_by_count":5,"area":null},{"id":"2506.19351","title":"In-Context Occam's Razor: How Transformers Prefer Simpler Hypotheses on the Fly","created":"2025-06-24","cited_by_count":5,"area":null},{"id":"2512.16902","title":"In-Context Algebra","created":"2025-12-18","cited_by_count":5,"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":"2605.05076","title":"High-Dimensional Statistics: Reflections on Progress and Open Problems","created":"2026-05-06","cited_by_count":4,"area":null},{"id":"2505.11004","title":"Illusion or Algorithm? Investigating Memorization, Emergence, and Symbolic Processing in In-Context Learning","created":"2025-05-16","cited_by_count":3,"area":null},{"id":"2506.16975","title":"Latent Concept Disentanglement in Transformer-based Language Models","created":"2025-06-20","cited_by_count":3,"area":null},{"id":"2508.11017","title":"Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics","created":"2025-08-14","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":"2509.22353","title":"Context and Diversity Matter: The Emergence of In-Context Learning in World Models","created":"2025-09-26","cited_by_count":3,"area":"wm"},{"id":"2510.16096","title":"Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization","created":"2025-10-17","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":"2605.12412","title":"Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space","created":"2026-05-12","cited_by_count":3,"area":null},{"id":"2602.00533","title":"Convergent World Representations and Divergent Tasks","created":"2026-01-31","cited_by_count":2,"area":null},{"id":"2602.19143","title":"Incremental Learning of Sparse Attention Patterns in Transformers","created":"2026-02-22","cited_by_count":2,"area":null},{"id":"2504.17068","title":"In-Context Learning can distort the relationship between sequence likelihoods and biological fitness","created":"2025-04-23","cited_by_count":1,"area":null},{"id":"2505.09855","title":"An evolutionary perspective on modes of learning in Transformers","created":"2025-05-14","cited_by_count":1,"area":null},{"id":"2506.04289","title":"Relational reasoning and inductive bias in transformers and large language models","created":"2025-06-04","cited_by_count":1,"area":"lr"},{"id":"2506.23146","title":"Learning-to-Context Slope: Evaluating In-Context Learning Effectiveness Beyond Performance Illusions","created":"2025-06-29","cited_by_count":1,"area":null},{"id":"2508.00385","title":"Multi-Layer Attention is the Amplifier of Demonstration Effectiveness","created":"2025-08-01","cited_by_count":1,"area":null},{"id":"2509.21534","title":"A circuit for predicting hierarchical structure in-context in Large Language Models","created":"2025-09-25","cited_by_count":1,"area":null},{"id":"2510.21408","title":"Large Language Models as Model Organisms for Human Associative Learning","created":"2025-10-24","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":"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":"2607.17060","title":"What does a Bayes-filtered transformer believe? A predictive Monte Carlo approach","created":"2026-07-19","cited_by_count":1,"area":null},{"id":"2506.02139","title":"The Unified Cognitive Consciousness Theory for Language Models: Anchoring Semantics, Thresholds of Activation, and Emergent Reasoning","created":"2025-06-02","cited_by_count":0,"area":"lr"},{"id":"2602.08294","title":"When Does Context Help? Error Dynamics of Contextual Information in Large Language Models","created":"2026-02-09","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":"2603.15248","title":"Mechanistic Foundations of Goal-Directed Control","created":"2026-03-16","cited_by_count":0,"area":"mechinterp"},{"id":"2604.01601","title":"Contrast Matters: Understanding Robustness of In-Context Fine-Tuning to Target-Context Relatedness","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2605.18281","title":"Temporal Task Diversity: Inductive Biases Under Non-Stationarity in Synthetic Sequence Modelling","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2606.01302","title":"Structure and Scale in Simplicial Sequence Modelling","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2606.07568","title":"A Systematic Study of Behavioral Cloning for Scientific Data Annotation","created":"2026-05-26","cited_by_count":0,"area":"offlinerl"},{"id":"2608.24460","title":"Shortcut Before Circuit: Document Statistics Time In-Context Conflict Resolution","created":"2026-08-25","cited_by_count":0,"area":null}],"next_cursor":null}