Papers
Improving Adaptivity via Over-Parameterization in Sequence Models
Yicheng Li, Qian Lin
Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
Shiji Zhao, Ranjie Duan, Xizhe Wang et al.
Improving Alignment and Robustness with Circuit Breakers
Andy Zou, Long Phan, Justin Wang et al.
Improving Context-Aware Preference Modeling for Language Models
Silviu Pitis, Ziang Xiao, Nicolas Le Roux et al.
Improving Decision Sparsity
Yiyang Sun, Tong Wang, Cynthia Rudin
Improving Deep Learning Optimization through Constrained Parameter Regularization
Jörg K.H. Franke, Michael Hefenbrock, Gregor Koehler et al.
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Hongyao Tang, Glen Berseth
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
Jayden Teoh, Wenjun Li, Pradeep Varakantham
Improving Equivariant Model Training via Constraint Relaxation
Stefanos Pertigkiozoglou, Evangelos Chatzipantazis, Shubhendu Trivedi et al.
Improving Generalization and Convergence by Enhancing Implicit Regularization
Mingze Wang, Jinbo Wang, Haotian He et al.
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
Hao Zhang, Chenglin Li, Nuowen Kan et al.
Improving Generalization of Dynamic Graph Learning via Environment Prompt
Kuo Yang, Zhengyang Zhou, Qihe Huang et al.
Improving Gloss-free Sign Language Translation by Reducing Representation Density
Jinhui Ye, Xing Wang, Wenxiang Jiao et al.
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Jihao Andreas Lin, Shreyas Padhy, Bruno Mlodozeniec et al.
Improving Neural Network Surface Processing with Principal Curvatures
Josquin Harrison, James Benn, Maxime Sermesant
Improving Neural ODE Training with Temporal Adaptive Batch Normalization
Su Zheng, Zhengqi Gao, Fan-Keng Sun et al.
Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective
Yibo Miao, Yinpeng Dong, Jinlai Zhang et al.
Improving robustness to corruptions with multiplicative weight perturbations
Trung Trinh, Markus Heinonen, Luigi Acerbi et al.
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees
Taejong Joo, Diego Klabjan
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders
Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith et al.
Improving Subgroup Robustness via Data Selection
Saachi Jain, Kimia Hamidieh, Kristian Georgiev et al.
Improving Temporal Link Prediction via Temporal Walk Matrix Projection
Xiaodong Lu, Leilei Sun, Tongyu Zhu et al.
Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity
Kaja Gruntkowska, Alexander Tyurin, Peter Richtárik