Papers
11,015 papers found
Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards
Xiaoyu Yang, Jie Lu, En Yu
Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
Théo Vincent, Fabian Wahren, Jan Peters et al.
Adaptive backtracking line search
Joao V. Cavalcanti, Laurent Lessard, Ashia C. Wilson
Adaptive Batch Size for Privately Finding Second-Order Stationary Points
Daogao Liu, Kunal Talwar
Adaptive Camera Sensor for Vision Models
Eunsu Baek, Sung-hwan Han, Taesik Gong et al.
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
Yiding Jiang, Allan Zhou, Zhili Feng et al.
Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats
Jiaxin Wen, Vivek Hebbar, Caleb Larson et al.
Adaptive Energy Alignment for Accelerating Test-Time Adaptation
Wonjeong Choi, Do-Yeon Kim, Jungwuk Park et al.
Adaptive Gradient Clipping for Robust Federated Learning
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta et al.
Adaptive Length Image Tokenization via Recurrent Allocation
Shivam Duggal, Phillip Isola, Antonio Torralba et al.
Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise
Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov et al.
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
Yizhuo Ding, Ke Fan, Yikai Wang et al.
Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
Roberto Garcia, Jerry Weihong Liu, Daniel Sorvisto et al.
Adaptive Retention & Correction: Test-Time Training for Continual Learning
Haoran Chen, Micah Goldblum, Zuxuan Wu et al.
Adaptive Shrinkage Estimation for Personalized Deep Kernel Regression in Modeling Brain Trajectories
Vasiliki Tassopoulou, Haochang Shou, Christos Davatzikos
Adaptive teachers for amortized samplers
Minsu Kim, Sanghyeok Choi, Taeyoung Yun et al.
Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son
AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
Yehonathan Refael, Jonathan Svirsky, Boris Shustin et al.
AdaWM: Adaptive World Model based Planning for Autonomous Driving
Hang Wang, Xin Ye, Feng Tao et al.
ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification
Xiao Li, Wenxuan Sun, Huanran Chen et al.
Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models
Zeman Li, Xinwei Zhang, Peilin Zhong et al.
Adding Conditional Control to Diffusion Models with Reinforcement Learning
Yulai Zhao, Masatoshi Uehara, Gabriele Scalia et al.
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models
Yoad Tewel, Rinon Gal, Dvir Samuel et al.
Addressing Label Shift in Distributed Learning via Entropy Regularization​
Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao et al.
A Decade's Battle on Dataset Bias: Are We There Yet?
Zhuang Liu, Kaiming He