{"total":55,"rows":[{"id":"2305.08298","title":"Symbol tuning improves in-context learning in language models","created":"2023-05-15","cited_by_count":75,"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":"2106.02940","title":"Same State, Different Task: Continual Reinforcement Learning without Interference","created":"2021-06-05","cited_by_count":43,"area":null},{"id":"2211.03318","title":"Fixing Model Bugs with Natural Language Patches","created":"2022-11-07","cited_by_count":33,"area":null},{"id":"2110.14057","title":"Meta-learning with an Adaptive Task Scheduler","created":"2021-10-26","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":"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":"2405.03547","title":"Position: Leverage Foundational Models for Black-Box Optimization","created":"2024-05-06","cited_by_count":21,"area":null},{"id":"2101.02523","title":"Few-Shot Learning with Class Imbalance","created":"2021-01-07","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":"2207.06046","title":"Learning Deep Time-index Models for Time Series Forecasting","created":"2022-07-13","cited_by_count":18,"area":null},{"id":"2204.05449","title":"Neural Processes with Stochastic Attention: Paying more attention to the context dataset","created":"2022-04-11","cited_by_count":16,"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":"2501.13075","title":"Evolution and The Knightian Blindspot of Machine Learning","created":"2025-01-22","cited_by_count":11,"area":null},{"id":"2106.15367","title":"MAML is a Noisy Contrastive Learner in Classification","created":"2021-06-29","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":"2108.02842","title":"Multimodal Meta-Learning for Time Series Regression","created":"2021-08-05","cited_by_count":7,"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":"2405.11467","title":"AdaAugment: A Tuning-Free and Adaptive Approach to Enhance Data Augmentation","created":"2024-05-19","cited_by_count":7,"area":null},{"id":"2407.14732","title":"Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training","created":"2024-07-20","cited_by_count":7,"area":null},{"id":"2204.00327","title":"Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations","created":"2022-04-01","cited_by_count":6,"area":null},{"id":"2206.01944","title":"Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile","created":"2022-06-04","cited_by_count":6,"area":null},{"id":"2509.15810","title":"Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering","created":"2025-09-19","cited_by_count":6,"area":null},{"id":"2211.02642","title":"A Meta-GNN approach to personalized seizure detection and classification","created":"2022-11-01","cited_by_count":5,"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":"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":"2311.14756","title":"Task-Distributionally Robust Data-Free Meta-Learning","created":"2023-11-23","cited_by_count":4,"area":null},{"id":"2109.08754","title":"Semi-Supervised Few-Shot Intent Classification and Slot Filling","created":"2021-09-17","cited_by_count":3,"area":null},{"id":"2110.09374","title":"Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning","created":"2021-10-18","cited_by_count":3,"area":null},{"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":"2405.16124","title":"Unsupervised Meta-Learning via In-Context Learning","created":"2024-05-25","cited_by_count":3,"area":null},{"id":"2507.17079","title":"Few-Shot Learning in Video and 3D Object Detection: A Survey","created":"2025-07-22","cited_by_count":2,"area":null},{"id":"2101.09819","title":"Meta-Regularization by Enforcing Mutual-Exclusiveness","created":"2021-01-24","cited_by_count":1,"area":null},{"id":"2109.07920","title":"On the inductive biases of deep domain adaptation","created":"2021-09-16","cited_by_count":1,"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":"2205.12013","title":"Naive Few-Shot Learning: Uncovering the fluid intelligence of machines","created":"2022-05-24","cited_by_count":1,"area":null},{"id":"2406.05887","title":"Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach","created":"2024-06-09","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":"2205.01924","title":"Zero-Episode Few-Shot Contrastive Predictive Coding: Solving intelligence tests without prior training","created":"2022-05-04","cited_by_count":0,"area":null},{"id":"2205.08755","title":"Persian Natural Language Inference: A Meta-learning approach","created":"2022-05-18","cited_by_count":0,"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":"2211.00110","title":"A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?","created":"2022-10-31","cited_by_count":0,"area":null},{"id":"2212.14094","title":"Wormhole MAML: Meta-Learning in Glued Parameter Space","created":"2022-12-28","cited_by_count":0,"area":null},{"id":"2301.00181","title":"Smooth Mathematical Function from Compact Neural Networks","created":"2022-12-31","cited_by_count":0,"area":null},{"id":"2304.12921","title":"AwesomeMeta+: A Mixed-Prototyping Meta-Learning System Supporting AI Application Design Anywhere","created":"2023-04-24","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":"2306.09702","title":"A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning","created":"2023-06-16","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":"2402.16157","title":"Consensus learning: A novel decentralised ensemble learning paradigm","created":"2024-02-25","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":"2405.12299","title":"Perturbing the Gradient for Alleviating Meta Overfitting","created":"2024-05-20","cited_by_count":0,"area":null},{"id":"2409.17474","title":"Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification","created":"2024-09-26","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}