Papers
Improving CLIP Training with Language Rewrites
Lijie Fan, Dilip Krishnan, Phillip Isola et al.
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
Yi Ren, Samuel Lavoie, Michael Galkin et al.
Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
Oussama Boussif, Ghait Boukachab, Dan Assouline et al.
Improving Diffusion-Based Image Synthesis with Context Prediction
Ling Yang, Jingwei Liu, Shenda Hong et al.
Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
Alon Albalak, Colin A Raffel, William Yang Wang
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
Yixiao Zhou, Ruiqi Jia, Hongxiang Lin et al.
Improving Language Plasticity via Pretraining with Active Forgetting
Yihong Chen, Kelly Marchisio, Roberta Raileanu et al.
Improving multimodal datasets with image captioning
Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco et al.
Improving neural network representations using human similarity judgments
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel et al.
Improving Robustness with Adaptive Weight Decay
Mohammad Amin Ghiasi, Ali Shafahi, Reza Ardekani
Improving Self-supervised Molecular Representation Learning using Persistent Homology
Yuankai Luo, Lei Shi, Veronika Thost
Improving the Knowledge Gradient Algorithm
Le Yang, Siyang Gao, Chin Pang Ho
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
Rachel Redberg, Antti Koskela, Yu-Xiang Wang
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization
Aniket Murhekar, Zhuowen Yuan, Bhaskar Ray Chaudhury et al.
Incentives in Private Collaborative Machine Learning
Rachael Sim, Yehong Zhang, Nghia Hoang et al.
Incentivized Communication for Federated Bandits
Zhepei Wei, Chuanhao Li, Haifeng Xu et al.
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
Florian E. Dorner, Nikola Konstantinov, Georgi Pashaliev et al.
Incomplete Multimodality-Diffused Emotion Recognition
Yuanzhi Wang, Yong Li, Zhen Cui
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
Rie Johnson, Tong Zhang
In-Context Impersonation Reveals Large Language Models' Strengths and Biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto et al.
In-Context Learning Unlocked for Diffusion Models
Zhendong Wang, Yifan Jiang, Yadong Lu et al.
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
Yuzhou Cao, Hussein Mozannar, Lei Feng et al.
Individual Arbitrariness and Group Fairness
Carol Long, Hsiang Hsu, Wael Alghamdi et al.
Individualized Dosing Dynamics via Neural Eigen Decomposition
Stav Belogolovsky, Ido Greenberg, Danny Eytan et al.
Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
Kenneth Li, Oam Patel, Fernanda Viégas et al.