Papers
Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity
Ali Behrouz, Parsa Delavari, Farnoosh Hashemi
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
Kevin Frans, Seohong Park, Pieter Abbeel et al.
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.
Unveiling Privacy, Memorization, and Input Curvature Links
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
Zhankun Luo, Abolfazl Hashemi
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou et al.
Unveiling the Potential of AI for Nanomaterial Morphology Prediction
Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko et al.
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
Yunhao Zhang, Minghao Liu, Shengyang Zhou et al.
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers
Duo Peng, Qiuhong Ke, Jun Liu
UPOCR: Towards Unified Pixel-Level OCR Interface
Dezhi Peng, Zhenhua Yang, Jiaxin Zhang et al.
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai et al.
Using AI Uncertainty Quantification to Improve Human Decision-Making
Laura Marusich, Jonathan Bakdash, Yan Zhou et al.
Using Left and Right Brains Together: Towards Vision and Language Planning
Jun Cen, Chenfei Wu, Xiao Liu et al.
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
S Chandra Mouli, Danielle C. Maddix, Shima Alizadeh et al.
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval
Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer et al.
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection
Yuxin Li, Yaoxuan Feng, Bo Chen et al.
Value-Evolutionary-Based Reinforcement Learning
Pengyi Li, Jianye Hao, Hongyao Tang et al.
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
Tanmay Gautam, Youngsuk Park, Hao Zhou et al.
Variational Inference with Coverage Guarantees in Simulation-Based Inference
Yash Patel, Declan Mcnamara, Jackson Loper et al.
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong et al.
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
Hyunsu Kim, Yegon Kim, Hongseok Yang et al.
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan et al.
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
Zhen Qin, Weigao Sun, Dong Li et al.