{"total":106,"rows":[{"id":"2208.01066","title":"What Can Transformers Learn In-Context? A Case Study of Simple Function Classes","created":"2022-08-01","cited_by_count":715,"area":null},{"id":"2106.09647","title":"Deep Learning Through the Lens of Example Difficulty","created":"2021-06-17","cited_by_count":141,"area":null},{"id":"2309.07311","title":"Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs","created":"2023-09-13","cited_by_count":124,"area":null},{"id":"2307.14430","title":"Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models","created":"2023-07-26","cited_by_count":121,"area":null},{"id":"2410.11820","title":"Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws","created":"2024-10-15","cited_by_count":47,"area":null},{"id":"2303.06242","title":"HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations","created":"2023-03-10","cited_by_count":44,"area":null},{"id":"2307.06440","title":"No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models","created":"2023-07-12","cited_by_count":41,"area":null},{"id":"2210.06640","title":"Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities","created":"2022-10-13","cited_by_count":38,"area":null},{"id":"2502.09650","title":"Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples","created":"2025-02-11","cited_by_count":37,"area":"alignment"},{"id":"2111.12918","title":"ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification","created":"2021-11-25","cited_by_count":35,"area":null},{"id":"2301.00930","title":"Data Valuation Without Training of a Model","created":"2023-01-03","cited_by_count":35,"area":null},{"id":"2107.13741","title":"Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels","created":"2021-07-29","cited_by_count":32,"area":null},{"id":"2205.13323","title":"The Effect of Task Ordering in Continual Learning","created":"2022-05-26","cited_by_count":31,"area":null},{"id":"2302.05499","title":"CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition","created":"2023-02-10","cited_by_count":30,"area":null},{"id":"2106.08068","title":"An Analytical Theory of Curriculum Learning in Teacher-Student Networks","created":"2021-06-15","cited_by_count":27,"area":"distill"},{"id":"2201.07459","title":"PT4AL: Using Self-Supervised Pretext Tasks for Active Learning","created":"2022-01-19","cited_by_count":27,"area":null},{"id":"2403.10348","title":"Denoising Task Difficulty-based Curriculum for Training Diffusion Models","created":"2024-03-15","cited_by_count":27,"area":"diffusion"},{"id":"2207.08768","title":"Rank-based Decomposable Losses in Machine Learning: A Survey","created":"2022-07-18","cited_by_count":26,"area":null},{"id":"2304.03589","title":"On Efficient Training of Large-Scale Deep Learning Models: A Literature Review","created":"2023-04-07","cited_by_count":26,"area":null},{"id":"2506.11300","title":"Beyond Random Sampling: Efficient Language Model Pretraining via Curriculum Learning","created":"2025-06-12","cited_by_count":26,"area":null},{"id":"2408.14471","title":"A Practitioner's Guide to Continual Multimodal Pretraining","created":"2024-08-26","cited_by_count":23,"area":null},{"id":"2106.06080","title":"Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent","created":"2021-06-10","cited_by_count":21,"area":null},{"id":"2206.01278","title":"Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks","created":"2022-06-02","cited_by_count":21,"area":null},{"id":"2311.08886","title":"CLIMB: Curriculum Learning for Infant-inspired Model Building","created":"2023-11-15","cited_by_count":20,"area":null},{"id":"2108.11096","title":"Learning From Long-Tailed Data With Noisy Labels","created":"2021-08-25","cited_by_count":17,"area":null},{"id":"2207.05219","title":"Grounding Aleatoric Uncertainty for Unsupervised Environment Design","created":"2022-07-11","cited_by_count":16,"area":null},{"id":"2310.09518","title":"Instruction Tuning with Human Curriculum","created":"2023-10-14","cited_by_count":15,"area":null},{"id":"2102.12033","title":"Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks","created":"2021-02-24","cited_by_count":13,"area":null},{"id":"2108.07183","title":"Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology","created":"2021-08-16","cited_by_count":13,"area":null},{"id":"2111.11288","title":"SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise","created":"2021-11-22","cited_by_count":13,"area":null},{"id":"2303.01130","title":"Distillation from Heterogeneous Models for Top-K Recommendation","created":"2023-03-02","cited_by_count":13,"area":"distill"},{"id":"2603.04964","title":"Replaying pre-training data improves fine-tuning","created":"2026-03-05","cited_by_count":13,"area":null},{"id":"2110.05481","title":"Which Samples Should be Learned First: Easy or Hard?","created":"2021-10-11","cited_by_count":12,"area":null},{"id":"2106.04696","title":"Curriculum Design for Teaching via Demonstrations: Theory and Applications","created":"2021-06-08","cited_by_count":9,"area":"offlinerl"},{"id":"2211.15470","title":"Learning to Learn: How to Continuously Teach Humans and Machines","created":"2022-11-28","cited_by_count":9,"area":null},{"id":"2212.12712","title":"When Do Curricula Work in Federated Learning?","created":"2022-12-24","cited_by_count":9,"area":null},{"id":"2406.01589","title":"Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks","created":"2024-06-03","cited_by_count":9,"area":null},{"id":"2602.03018","title":"From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection","created":"2026-02-03","cited_by_count":9,"area":null},{"id":"2102.06406","title":"A Too-Good-to-be-True Prior to Reduce Shortcut Reliance","created":"2021-02-12","cited_by_count":7,"area":null},{"id":"2306.03511","title":"Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation","created":"2023-06-06","cited_by_count":7,"area":null},{"id":"2506.21393","title":"TableMoE: Neuro-Symbolic Routing for Structured Expert Reasoning in Multimodal Table Understanding","created":"2025-06-26","cited_by_count":7,"area":"lr"},{"id":"2510.12071","title":"Influence Dynamics and Stagewise Data Attribution","created":"2025-10-14","cited_by_count":7,"area":null},{"id":"2601.07087","title":"When Should We Introduce Safety Interventions During Pretraining?","created":"2026-01-11","cited_by_count":7,"area":"safety"},{"id":"2108.01662","title":"Uniform Sampling over Episode Difficulty","created":"2021-08-03","cited_by_count":6,"area":null},{"id":"2207.08525","title":"Angular Gap: Reducing the Uncertainty of Image Difficulty through Model Calibration","created":"2022-07-18","cited_by_count":6,"area":null},{"id":"2302.01049","title":"Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation","created":"2023-02-02","cited_by_count":6,"area":"distill"},{"id":"2309.14091","title":"On the Benefit of Optimal Transport for Curriculum Reinforcement Learning","created":"2023-09-25","cited_by_count":6,"area":null},{"id":"2203.10692","title":"Better Language Model with Hypernym Class Prediction","created":"2022-03-21","cited_by_count":5,"area":null},{"id":"2209.09658","title":"Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty","created":"2022-09-19","cited_by_count":5,"area":null},{"id":"2210.00313","title":"CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family","created":"2022-10-01","cited_by_count":5,"area":null},{"id":"2210.12499","title":"Training Dynamics for Curriculum Learning: A Study on Monolingual and Cross-lingual NLU","created":"2022-10-22","cited_by_count":5,"area":null},{"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":"2202.05531","title":"Cyclical Curriculum Learning","created":"2022-02-11","cited_by_count":4,"area":null},{"id":"2210.08442","title":"Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning","created":"2022-10-16","cited_by_count":4,"area":null},{"id":"2212.01452","title":"CLIP: Train Faster with Less Data","created":"2022-12-02","cited_by_count":4,"area":null},{"id":"2406.18373","title":"Dynamic Data Pruning for Automatic Speech Recognition","created":"2024-06-26","cited_by_count":4,"area":null},{"id":"2102.08581","title":"Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning","created":"2021-02-17","cited_by_count":3,"area":null},{"id":"2112.06510","title":"Do Data-based Curricula Work?","created":"2021-12-13","cited_by_count":3,"area":null},{"id":"2201.01164","title":"Interpretable Low-Resource Legal Decision Making","created":"2022-01-01","cited_by_count":3,"area":null},{"id":"2307.05747","title":"Integrating Curricula with Replays: Its Effects on Continual Learning","created":"2023-07-08","cited_by_count":3,"area":null},{"id":"2310.20121","title":"Ling-CL: Understanding NLP Models through Linguistic Curricula","created":"2023-10-31","cited_by_count":3,"area":null},{"id":"2410.15509","title":"Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training","created":"2024-10-20","cited_by_count":3,"area":null},{"id":"2411.00973","title":"Does the Definition of Difficulty Matter? Scoring Functions and their Role for Curriculum Learning","created":"2024-11-01","cited_by_count":3,"area":null},{"id":"2507.07907","title":"A statistical physics framework for optimal learning","created":"2025-07-10","cited_by_count":3,"area":null},{"id":"2106.10974","title":"Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier","created":"2021-06-21","cited_by_count":2,"area":null},{"id":"2107.11921","title":"Compensation Learning","created":"2021-07-26","cited_by_count":2,"area":null},{"id":"2210.08748","title":"Dual-Curriculum Teacher for Domain-Inconsistent Object Detection in Autonomous Driving","created":"2022-10-17","cited_by_count":2,"area":null},{"id":"2307.08859","title":"Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach","created":"2023-07-17","cited_by_count":2,"area":null},{"id":"2310.10124","title":"A Comprehensive Study of Privacy Risks in Curriculum Learning","created":"2023-10-16","cited_by_count":2,"area":null},{"id":"2405.17377","title":"How Do the Architecture and Optimizer Affect Representation Learning? On the Training Dynamics of Representations in Deep Neural Networks","created":"2024-05-27","cited_by_count":2,"area":null},{"id":"2504.11669","title":"Co-STAR: Collaborative Curriculum Self-Training with Adaptive Regularization for Source-Free Video Domain Adaptation","created":"2025-04-15","cited_by_count":2,"area":"mllm"},{"id":"2508.15475","title":"Influence-driven Curriculum Learning for Pre-training on Limited Data","created":"2025-08-21","cited_by_count":2,"area":null},{"id":"2603.22586","title":"A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks","created":"2026-03-23","cited_by_count":2,"area":null},{"id":"2103.00147","title":"Statistical Measures For Defining Curriculum Scoring Function","created":"2021-02-27","cited_by_count":1,"area":null},{"id":"2204.13849","title":"Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection","created":"2022-04-29","cited_by_count":1,"area":null},{"id":"2208.13946","title":"PercentMatch: Percentile-based Dynamic Thresholding for Multi-Label Semi-Supervised Classification","created":"2022-08-30","cited_by_count":1,"area":null},{"id":"2209.07606","title":"CES-KD: Curriculum-based Expert Selection for Guided Knowledge Distillation","created":"2022-09-15","cited_by_count":1,"area":"distill"},{"id":"2307.07412","title":"HuCurl: Human-induced Curriculum Discovery","created":"2023-07-14","cited_by_count":1,"area":null},{"id":"2312.15853","title":"Curricular and Cyclical Loss for Time Series Learning Strategy","created":"2023-12-26","cited_by_count":1,"area":null},{"id":"2401.07586","title":"Curriculum for Crowd Counting -- Is it Worthy?","created":"2024-01-15","cited_by_count":1,"area":null},{"id":"2402.14890","title":"Vygotsky Distance: Measure for Benchmark Task Similarity","created":"2024-02-22","cited_by_count":1,"area":null},{"id":"2403.13844","title":"Scheduled Knowledge Acquisition on Lightweight Vector Symbolic Architectures for Brain-Computer Interfaces","created":"2024-03-18","cited_by_count":1,"area":"distill"},{"id":"2404.03084","title":"Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience","created":"2024-04-03","cited_by_count":1,"area":null},{"id":"2407.19346","title":"Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment","created":"2024-07-27","cited_by_count":1,"area":null},{"id":"2510.13817","title":"What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale","created":"2025-09-24","cited_by_count":1,"area":null},{"id":"2604.24171","title":"POCA: Pareto-Optimal Curriculum Alignment for Visual Text Generation","created":"2026-04-27","cited_by_count":1,"area":null},{"id":"2605.11260","title":"Curriculum Learning-Guided Progressive Distillation in Large Language Models","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2106.14412","title":"Progressive Class-based Expansion Learning For Image Classification","created":"2021-06-28","cited_by_count":0,"area":null},{"id":"2109.07380","title":"DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning","created":"2021-09-15","cited_by_count":0,"area":"offlinerl"},{"id":"2206.00518","title":"Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning","created":"2022-06-01","cited_by_count":0,"area":null},{"id":"2207.03571","title":"A Study on the Predictability of Sample Learning Consistency","created":"2022-07-07","cited_by_count":0,"area":null},{"id":"2302.02119","title":"Diversity Induced Environment Design via Self-Play","created":"2023-02-04","cited_by_count":0,"area":null},{"id":"2302.05838","title":"Maneuver Decision-Making For Autonomous Air Combat Through Curriculum Learning And Reinforcement Learning With Sparse Rewards","created":"2023-02-12","cited_by_count":0,"area":null},{"id":"2312.00660","title":"Resource-constrained knowledge diffusion processes inspired by human peer learning","created":"2023-12-01","cited_by_count":0,"area":null},{"id":"2408.07243","title":"Leveraging Perceptual Scores for Dataset Pruning in Computer Vision Tasks","created":"2024-08-14","cited_by_count":0,"area":null},{"id":"2504.01737","title":"Enlightenment Period Improving DNN Performance","created":"2025-04-02","cited_by_count":0,"area":null},{"id":"2508.03031","title":"From Text to Trajectories: GPT-2 as an ODE Solver via In-Context","created":"2025-08-05","cited_by_count":0,"area":null},{"id":"2510.26792","title":"Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability","created":"2025-10-30","cited_by_count":0,"area":null},{"id":"2602.11040","title":"Learning Page Order in Shuffled WOO Releases","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2602.20296","title":"Learning to Solve Complex Problems via Dataset Decomposition","created":"2026-02-23","cited_by_count":0,"area":null}],"next_cursor":"100"}