All Papers

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

Songtao Feng, Ming Yin, Yu-Xiang Wang et al.

Improving SAM Requires Rethinking its Optimization Formulation

Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos et al.

Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps

Octave Mariotti, Oisin Mac Aodha, Hakan Bilen

Improving Sharpness-Aware Minimization by Lookahead

Runsheng Yu, Youzhi Zhang, James Kwok

Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment

Muhammad Sohail Danish, Muhammad Haris Khan, Muhammad Akhtar Munir et al.

Improving Spectral Snapshot Reconstruction with Spectral-Spatial Rectification

Jiancheng Zhang, Haijin Zeng, Yongyong Chen et al.

Improving Subject-Driven Image Synthesis with Subject-Agnostic Guidance

Kelvin C.K. Chan, Yang Zhao, Xuhui Jia et al.

Improving Text-guided Object Inpainting with Semantic Pre-inpainting

Yifu Chen, Jingwen Chen, Yingwei Pan et al.

Improving the Adversarial Transferability of Vision Transformers with Virtual Dense Connection

Jianping Zhang, Yizhan Huang, Zhuoer Xu et al.

Improving the Convergence of Dynamic NeRFs via Optimal Transport

Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham et al.

Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation

Haojie Zhang, Yongyi Su, Xun Xu et al.

Improving the Robustness of Knowledge-Grounded Dialogue via Contrastive Learning

Jiaan Wang, JIanfeng Qu, Kexin Wang et al.

Improving Token-Based World Models with Parallel Observation Prediction

Lior Cohen, Kaixin Wang, Bingyi Kang et al.

Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture

Huijie Zhang, Yifu Lu, Ismail Alkhouri et al.

Improving Transferability for Cross-Domain Trajectory Prediction via Neural Stochastic Differential Equation

Daehee Park, Jaewoo Jeong, Kuk-Jin Yoon

Improving Transferable Targeted Adversarial Attacks with Model Self-Enhancement

Han Wu, Guanyan Ou, Weibin Wu et al.

Improving Transformers with Dynamically Composable Multi-Head Attention

Da Xiao, Qingye Meng, Shengping Li et al.

Improving Unsupervised Domain Adaptation: A Pseudo-Candidate Set Approach

Aveen Dayal, Rishabh Lalla, Linga Reddy Cenkeramaddi et al.

Improving Unsupervised Hierarchical Representation with Reinforcement Learning

Ruyi An, Yewen Li, Xu He et al.

Improving Video Segmentation via Dynamic Anchor Queries

Yikang Zhou, Tao Zhang, Xiangtai Li et al.

Improving Virtual Try-On with Garment-focused Diffusion Models

Siqi Wan, Yehao Li, Jingwen Chen et al.

Improving Vision and Language Concepts Understanding with Multimodal Counterfactual Samples

Chengen Lai, Shengli Song, Sitong Yan et al.

Improving Visual Recognition with Hyperbolical Visual Hierarchy Mapping

Hyeongjun Kwon, Jinhyun Jang, Jin Kim et al.

Improving Zero-Shot Generalization for CLIP with Variational Adapter

Ziqian Lu, Fengli Shen, Mushui Liu 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.

IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers

Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh

In2SET: Intra-Inter Similarity Exploiting Transformer for Dual-Camera Compressive Hyperspectral Imaging

Xin Wang, Lizhi Wang, Xiangtian Ma et al.

Incentive-Aware Federated Learning with Training-Time Model Rewards

Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar et al.

Incentivized Learning in Principal-Agent Bandit Games

Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren et al.

InceptionNeXt: When Inception Meets ConvNeXt

Weihao Yu, Pan Zhou, Shuicheng Yan et al.

Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding

Inconsistency-Based Data-Centric Active Open-Set Annotation

Ruiyu Mao, Ouyang Xu, Yunhui Guo

In-context Autoencoder for Context Compression in a Large Language Model

Tao Ge, Hu Jing, Lei Wang et al.

In-context Convergence of Transformers

Yu Huang, Yuan Cheng, Yingbin LIANG

In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought

sili huang, Jifeng Hu, Hechang Chen et al.

In-context Exploration-Exploitation for Reinforcement Learning

Zhenwen Dai, Federico Tomasi, Sina Ghiassian

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.

In-Context Language Learning: Architectures and Algorithms

Ekin Akyürek, Bailin Wang, Yoon Kim et al.

In-Context Learning Agents Are Asymmetric Belief Updaters

Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.

In-Context Learning Dynamics with Random Binary Sequences

Eric Bigelow, Ekdeep Singh Lubana, Robert Dick et al.

In-Context Learning Learns Label Relationships but Is Not Conventional Learning

Jannik Kossen, Yarin Gal, Tom Rainforth

In-context Learning on Function Classes Unveiled for Transformers

Zhijie Wang, Bo Jiang, Shuai Li

In-Context Learning through the Bayesian Prism

Madhur Panwar, Kabir Ahuja, Navin Goyal

In-Context Matting

He Guo, Zixuan Ye, Zhiguo Cao et al.

In-Context Pretraining: Language Modeling Beyond Document Boundaries

Weijia Shi, Sewon Min, Maria Lomeli et al.

In-Context Principle Learning from Mistakes

Tianjun Zhang, Aman Madaan, Luyu Gao et al.

In-Context Reinforcement Learning for Variable Action Spaces

Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov et al.

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

Shiqi Chen, Miao Xiong, Junteng Liu et al.