Papers
11,955 papers found
Improving Diffusion Models for Authentic Virtual Try-on in the Wild
Yisol Choi, Sangkyung Kwak, Kyungmin Lee et al.
Improving Domain Generalization with Domain Relations
Huaxiu Yao, Xinyu Yang, Xinyi Pan et al.
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux, Friedemann Zenke
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Rui Zheng, Wei Shen, Yuan Hua et al.
Improving Geo-diversity of Generated Images with Contextualized Vendi Score Guidance
Reyhane Askari Hemmat, Melissa Hall, Alicia Yi Sun et al.
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization
Yifei Yang, Wonjun Lee, Dongmian Zou et al.
Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer, Joshua Romoff, Glen Berseth
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li et al.
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Ziming Hong, Zhenyi Wang, Li Shen et al.
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov et al.
Improving protein optimization with smoothed fitness landscapes
Andrew Kirjner, Jason Yim, Raman Samusevich et al.
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures
Sayanton V. Dibbo, Adam Breuer, Juston Moore et al.
Improving the Convergence of Dynamic NeRFs via Optimal Transport
Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham et al.
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
Marco Mistretta, Alberto Baldrati, Marco Bertini et al.
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
Zhaoyuan Yang, Zhengyang Yu, Zhiwei Xu et al.
Incentive-Aware Federated Learning with Training-Time Model Rewards
Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar et al.
Incentivized Truthful Communication for Federated Bandits
Zhepei Wei, Chuanhao Li, Tianze Ren et al.
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Hu Jing, Lei Wang et al.
In-context Exploration-Exploitation for Reinforcement Learning
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-Context Learning Dynamics with Random Binary Sequences
Eric J Bigelow, Ekdeep Singh Lubana, Robert P. Dick et al.
In-Context Learning Learns Label Relationships but Is Not Conventional Learning
Jannik Kossen, Yarin Gal, Tom Rainforth
In-Context Learning through the Bayesian Prism
Madhur Panwar, Kabir Ahuja, Navin Goyal
In-Context Pretraining: Language Modeling Beyond Document Boundaries
Weijia Shi, Sewon Min, Maria Lomeli et al.
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Haobo SONG, Hao Zhao, Soumajit Majumder et al.
Incremental Randomized Smoothing Certification
Shubham Ugare, Tarun Suresh, Debangshu Banerjee et al.