Curriculum Learning

AAAI 2025arXiv:2412.09441

#2

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao et al.

16

ICCV 2025arXiv:2508.06492

#3

Effective Training Data Synthesis for Improving MLLM Chart Understanding

Yuwei Yang, Zeyu Zhang, Yunzhong Hou et al.

chart understandingmultimodal large language modelsdata synthesis pipelinesynthetic chart generation+3

10

ICLR 2024arXiv:2503.16799

#4

Causally Aligned Curriculum Learning

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

7

NeurIPS 2025arXiv:2506.15893

#5

Curriculum Abductive Learning

Wen-Chao Hu, Qi-Jie Li, Lin-Han Jia et al.

When Does Curriculum Learning Help? A Theoretical Perspective

Raman Arora, Yunjuan Wang, Kaibo Zhang

Safety-Prioritizing Curricula for Constrained Reinforcement Learning

Cevahir Koprulu, Thiago Simão, Nils Jansen et al.

Formal Models of Active Learning from Contrastive Examples

Farnam Mansouri, Hans Simon, Adish Singla et al.

active learningcontrastive examplessample complexityconcept classes+3

curriculum learningdataset decompositionteacher-student frameworkstep-by-step reasoning+3

#9

Bandit Guided Submodular Curriculum for Adaptive Subset Selection

Prateek Chanda, Prayas Agrawal, Saral Sureka et al.

LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought

Cheng Yan, Felix Mohr, Tom Viering

Learning to Solve Complex Problems via Dataset Decomposition

Wanru Zhao, Lucas Page-Caccia, Zhengyan Shi et al.

NeurIPS 2025

nonlinear model classeslinear measurementshilbert spacesgeneralization bounds+4

#12

Curriculum Design for Trajectory-Constrained Agent: Compressing Chain-of-Thought Tokens in LLMs

Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla

Learning with Structural Labels for Learning with Noisy Labels

Noo-ri Kim, Jin-Seop Lee, Jee-Hyong Lee

SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers

Ioannis Kakogeorgiou, Spyros Gidaris, Konstantinos Karantzalos et al.

A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples

Ben Adcock, Juan Cardenas, Nick Dexter

ICML 2024

AAAI 2024arXiv:2302.13020

#16

Optimal Task Order for Continual Learning of Multiple Tasks

Ziyan Li, Naoki Hiratani

Unsupervised Order Learning

Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim

Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks

Xiaofan Que, Qi Yu

DCLP: Neural Architecture Predictor with Curriculum Contrastive Learning

Shenghe Zheng, Hongzhi Wang, Tianyu Mu

AAAI 2025arXiv:2504.17474

#20

A Closer Look at Curriculum Adversarial Training: From an Online Perspective

Lianghe Shi, Weiwei Liu

Quality-Diversity Generative Sampling for Learning with Synthetic Data

Allen Chang, Matthew C. Fontaine, Serena Booth et al.

Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled Yet Hard-to-Learn Samples in Noisy Data

Weiran Pan, Wei Wei, Feida Zhu et al.

curriculum learningbenchmark evaluationcomputer visionnatural language processing+4

#23

CurBench: Curriculum Learning Benchmark

Yuwei Zhou, Zirui Pan, Xin Wang et al.

ICML 2024

ECCV 2024arXiv:2312.05328

#24

Temporally Consistent Object-Centric Learning by Contrasting Slots

Anna Manasyan, Maximilian Seitzer, Filip Radovic et al.

Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding

Talfan Evans, Shreya Pathak, Hamza Merzic et al.

active learningdata efficiencyvisual understandingmultimodal models+4