Papers
11,015 papers found
DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
Zaid Khan, Elias Stengel-Eskin, Jaemin Cho et al.
DataGen: Unified Synthetic Dataset Generation via Large Language Models
Yue Huang, Siyuan Wu, Chujie Gao et al.
DataMan: Data Manager for Pre-training Large Language Models
Ru Peng, Kexin Yang, Yawen Zeng et al.
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
Jiasheng Ye, Peiju Liu, Tianxiang Sun et al.
Data Pruning by Information Maximization
Haoru Tan, Sitong Wu, Wei Huang et al.
Data Scaling Laws in Imitation Learning for Robotic Manipulation
Fanqi Lin, Yingdong Hu, Pingyue Sheng et al.
Data Selection via Optimal Control for Language Models
Yuxian Gu, Li Dong, Hongning Wang et al.
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
Data Shapley in One Training Run
Jiachen T. Wang, Prateek Mittal, Dawn Song et al.
Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning
Wassim Bouaziz, Nicolas Usunier, El-Mahdi El-Mhamdi
Data Unlearning in Diffusion Models
Silas Alberti, Kenan Hasanaliyev, Manav Shah et al.
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
Changdae Oh, Yixuan Li, Kyungwoo Song et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, ziyang zhang, Zheng Xu et al.
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Tatzel, Bálint Mucsányi, Osane Hackel et al.
dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
Emanuele Zangrando, Sara Venturini, Francesco Rinaldi et al.
Decentralized Optimization with Coupled Constraints
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev et al.
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis et al.
DeciMamba: Exploring the Length Extrapolation Potential of Mamba
Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein et al.
Decision Information Meets Large Language Models: The Future of Explainable Operations Research
Yansen Zhang, Qingcan Kang, Wing Yin YU et al.
Decision Tree Induction Through LLMs via Semantically-Aware Evolution
Tennison Liu, Nicolas Huynh, Mihaela van der Schaar
Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
Sijin Chen, Omar Hagrass, Jason Matthew Klusowski