{"total":55,"rows":[{"id":"2211.14238","title":"Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time","created":"2022-11-25","cited_by_count":90,"area":null},{"id":"2210.05775","title":"C-Mixup: Improving Generalization in Regression","created":"2022-10-11","cited_by_count":57,"area":null},{"id":"2106.02695","title":"Meta-Learning with Fewer Tasks through Task Interpolation","created":"2021-06-04","cited_by_count":45,"area":null},{"id":"2106.10189","title":"Adversarial Training Helps Transfer Learning via Better Representations","created":"2021-06-18","cited_by_count":36,"area":null},{"id":"2305.15930","title":"End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes","created":"2023-05-25","cited_by_count":32,"area":null},{"id":"2102.04002","title":"Meta Discovery: Learning to Discover Novel Classes given Very Limited Data","created":"2021-02-08","cited_by_count":31,"area":null},{"id":"2212.10888","title":"A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability","created":"2022-12-21","cited_by_count":31,"area":null},{"id":"2208.09913","title":"A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective","created":"2022-08-21","cited_by_count":27,"area":null},{"id":"2205.01500","title":"Meta Learning for Natural Language Processing: A Survey","created":"2022-05-03","cited_by_count":26,"area":null},{"id":"2305.02644","title":"Neuralizer: General Neuroimage Analysis without Re-Training","created":"2023-05-04","cited_by_count":24,"area":null},{"id":"2106.16245","title":"How to Train Your MAML to Excel in Few-Shot Classification","created":"2021-06-30","cited_by_count":22,"area":null},{"id":"2110.00715","title":"An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset","created":"2021-10-02","cited_by_count":18,"area":null},{"id":"2203.04905","title":"What Matters For Meta-Learning Vision Regression Tasks?","created":"2022-03-09","cited_by_count":18,"area":null},{"id":"2303.04379","title":"HappyMap: A Generalized Multi-calibration Method","created":"2023-03-08","cited_by_count":18,"area":null},{"id":"2107.00197","title":"Few-Shot Learning with a Strong Teacher","created":"2021-07-01","cited_by_count":16,"area":null},{"id":"2306.14770","title":"ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion","created":"2023-06-26","cited_by_count":16,"area":"diffusion"},{"id":"2202.02929","title":"Model-Based Offline Meta-Reinforcement Learning with Regularization","created":"2022-02-07","cited_by_count":15,"area":"offlinerl"},{"id":"2206.02792","title":"FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data","created":"2022-06-06","cited_by_count":13,"area":null},{"id":"2407.19523","title":"Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation","created":"2024-07-28","cited_by_count":13,"area":null},{"id":"2109.13576","title":"Multimodality in Meta-Learning: A Comprehensive Survey","created":"2021-09-28","cited_by_count":11,"area":null},{"id":"2307.08924","title":"Towards Task Sampler Learning for Meta-Learning","created":"2023-07-18","cited_by_count":11,"area":null},{"id":"2107.02378","title":"Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks","created":"2021-07-06","cited_by_count":9,"area":null},{"id":"2210.05185","title":"Meta-Learning with Self-Improving Momentum Target","created":"2022-10-11","cited_by_count":9,"area":null},{"id":"2306.08126","title":"PersonaPKT: Building Personalized Dialogue Agents via Parameter-efficient Knowledge Transfer","created":"2023-06-13","cited_by_count":9,"area":null},{"id":"2203.11670","title":"Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation","created":"2022-03-22","cited_by_count":8,"area":null},{"id":"2312.05771","title":"Hacking Task Confounder in Meta-Learning","created":"2023-12-10","cited_by_count":8,"area":null},{"id":"2205.09990","title":"Set-based Meta-Interpolation for Few-Task Meta-Learning","created":"2022-05-20","cited_by_count":7,"area":null},{"id":"2205.11110","title":"Meta-Learning Regrasping Strategies for Physical-Agnostic Objects","created":"2022-05-23","cited_by_count":7,"area":null},{"id":"2311.06673","title":"Dream to Adapt: Meta Reinforcement Learning by Latent Context Imagination and MDP Imagination","created":"2023-11-11","cited_by_count":6,"area":null},{"id":"2501.05635","title":"Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport","created":"2025-01-10","cited_by_count":6,"area":null},{"id":"2502.14158","title":"Dual-level Mixup for Graph Few-shot Learning with Fewer Tasks","created":"2025-02-19","cited_by_count":5,"area":null},{"id":"2506.19540","title":"Overtuning in Hyperparameter Optimization","created":"2025-06-24","cited_by_count":5,"area":null},{"id":"2305.07892","title":"DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning","created":"2023-05-13","cited_by_count":4,"area":null},{"id":"2305.10309","title":"MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks","created":"2023-05-17","cited_by_count":4,"area":null},{"id":"2307.05948","title":"Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation","created":"2023-07-12","cited_by_count":4,"area":null},{"id":"2501.00195","title":"Towards Unraveling and Improving Generalization in World Models","created":"2024-12-31","cited_by_count":4,"area":"wm"},{"id":"2305.07269","title":"Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction","created":"2023-05-12","cited_by_count":3,"area":null},{"id":"2308.13049","title":"Bayesian Exploration Networks","created":"2023-08-24","cited_by_count":3,"area":null},{"id":"2405.16124","title":"Unsupervised Meta-Learning via In-Context Learning","created":"2024-05-25","cited_by_count":3,"area":null},{"id":"2210.05572","title":"Knowledge-Driven New Drug Recommendation","created":"2022-10-11","cited_by_count":2,"area":null},{"id":"2402.08221","title":"MetaTra: Meta-Learning for Generalized Trajectory Prediction in Unseen Domain","created":"2024-02-13","cited_by_count":2,"area":null},{"id":"2410.01655","title":"Reevaluating Meta-Learning Optimization Algorithms Through Contextual Self-Modulation","created":"2024-10-02","cited_by_count":2,"area":null},{"id":"2506.08906","title":"Hyperbolic Dual Feature Augmentation for Open-Environment","created":"2025-06-10","cited_by_count":2,"area":null},{"id":"2202.12326","title":"Towards Better Meta-Initialization with Task Augmentation for Kindergarten-aged Speech Recognition","created":"2022-02-24","cited_by_count":1,"area":null},{"id":"2204.03511","title":"Interval Bound Interpolation for Few-shot Learning with Few Tasks","created":"2022-04-07","cited_by_count":1,"area":null},{"id":"2301.07927","title":"Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning","created":"2023-01-19","cited_by_count":1,"area":null},{"id":"2409.02486","title":"Boosting Generalizability towards Zero-Shot Cross-Dataset Single-Image Indoor Depth by Meta-Initialization","created":"2024-09-04","cited_by_count":1,"area":null},{"id":"2409.08474","title":"Rethinking Meta-Learning from a Learning Lens","created":"2024-09-13","cited_by_count":1,"area":null},{"id":"2206.04335","title":"Learning to generate imaginary tasks for improving generalization in meta-learning","created":"2022-06-09","cited_by_count":0,"area":null},{"id":"2210.06341","title":"TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding","created":"2022-09-26","cited_by_count":0,"area":null},{"id":"2210.07098","title":"Meta-learning Based Short-Term Passenger Flow Prediction for Newly-Operated Urban Rail Transit Stations","created":"2022-10-13","cited_by_count":0,"area":null},{"id":"2306.08460","title":"Improving Generalization in Meta-Learning via Meta-Gradient Augmentation","created":"2023-06-14","cited_by_count":0,"area":null},{"id":"2310.13085","title":"Unsupervised Representation Learning to Aid Semi-Supervised Meta Learning","created":"2023-10-19","cited_by_count":0,"area":null},{"id":"2402.18599","title":"Meta-Task: A Method-Agnostic Framework for Learning to Regularize in Few-Shot Learning","created":"2024-02-27","cited_by_count":0,"area":null},{"id":"2411.06746","title":"Neuromodulated Meta-Learning","created":"2024-11-11","cited_by_count":0,"area":null}],"next_cursor":null}