2025 Papers
21,856 papers found • Page 409 of 438
Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
Yujie Zhu, Charles Hepburn, Matthew Thorpe et al.
Uncertainty-Calibrated Prediction of Randomly-Timed Biomarker Trajectories with Conformal Bands
Vasiliki Tassopoulou, Charis Stamouli, Haochang Shou et al.
Uncertainty-Driven Expert Control: Enhancing the Reliability of Medical Vision-Language Models
Xiao Liang, Di Wang, Zhicheng Jiao et al.
Uncertainty Estimation by Flexible Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
Dominik Fuchsgruber, Tom Wollschläger, Johannes Bordne et al.
Uncertainty Estimation on Graphs with Structure Informed Stochastic Partial Differential Equations
Fred Xu, Thomas Markovich
Uncertainty-Guided Exploration for Efficient AlphaZero Training
Scott Cheng, Meng-Yu Tsai, Ding-Yong Hong et al.
Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model
Leheng Zhang, Weiyi You, Kexuan Shi et al.
Uncertainty Herding: One Active Learning Method for All Label Budgets
Wonho Bae, Danica Sutherland, Gabriel Oliveira
Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
Xingyu Ren, Pengwei Liu, Pengkai Wang et al.
Uncertainty-Instructed Structure Injection for Generalizable HD Map Construction
Xiaolu Liu, Ruizi Yang, Song Wang et al.
Uncertainty Meets Diversity: A Comprehensive Active Learning Framework for Indoor 3D Object Detection
Jiangyi Wang, Na Zhao
Uncertainty modeling for fine-tuned implicit functions
Anna Susmelj, Mael Macuglia, Natasa Tagasovska et al.
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows
Adriel Sosa Marco, John D. Kirwan, Alexia Toumpa et al.
Uncertainty Quantification for LLM-Based Survey Simulations
Chengpiao Huang, Yuhang Wu, Kaizheng Wang
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
Frank Shih, Zhenghao Jiang, Faming Liang
Uncertainty Quantification with the Empirical Neural Tangent Kernel
Joseph Wilson, Chris van der Heide, Liam Hodgkinson et al.
Uncertainty-quantified Rollout Policy Adaptation for Unlabelled Cross-domain Video Temporal Grounding
Jian Hu, Zixu Cheng, Shaogang Gong et al.
Uncertainty-Sensitive Privileged Learning
Fan-Ming Luo, Lei Yuan, Yang Yu
Uncertainty Weighted Gradients for Model Calibration
Jinxu Lin, Linwei Tao, Minjing Dong et al.
UnCLe: Towards Scalable Dynamic Causal Discovery in Non-linear Temporal Systems
Tingzhu Bi, Yicheng Pan, Xinrui Jiang et al.
Uncommon Belief in Rationality
Qi Shi, Pavel Naumov
UnCommon Objects in 3D
Xingchen Liu, Piyush Tayal, Jianyuan Wang et al.
Unconstrained Robust Online Convex Optimization
Jiujia Zhang, Ashok Cutkosky
Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback
Jing Dong, Baoxiang Wang, Yaoliang Yu
Uncover Governing Law of Pathology Propagation Mechanism Through A Mean-Field Game
Tingting Dan, Zhihao Fan, Guorong Wu
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
Gavin McCracken, Gabriela Moisescu-Pareja, Vincent Létourneau et al.
Uncovering Gaps in How Humans and LLMs Interpret Subjective Language
Erik Jones, Arjun Patrawala, Jacob Steinhardt
Uncovering Latent Memories in Large Language Models
Sunny Duan, Mikail Khona, Abhiram Iyer et al.
Uncovering LLM-Generated Code: A Zero-Shot Synthetic Code Detector via Code Rewriting
Tong Ye, Yangkai Du, Tengfei Ma et al.
Uncovering Overfitting in Large Language Model Editing
Mengqi Zhang, Xiaotian Ye, Qiang Liu et al.
Uncovering the Spectral Bias in Diagonal State Space Models
Ruben Solozabal, Velibor Bojkovic, Hilal AlQuabeh et al.
Uncover Treasures in DCT: Advancing JPEG Quality Enhancement by Exploiting Latent Correlations
jing Yang, Qunliang Xing, Mai Xu et al.
Underdamped Diffusion Bridges with Applications to Sampling
Denis Blessing, Julius Berner, Lorenz Richter et al.
Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning
Rongzhe Wei, Mufei Li, Mohsen Ghassemi et al.
Undermining Mental Proof: How AI Can Make Cooperation Harder by Making Thinking Easier
Zachary Wojtowicz, Simon DeDeo
Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
Xiaoyu Yue, ZiDong Wang, Yuqing Wang et al.
Understanding Adam Requires Better Rotation Dependent Assumptions
Tianyue Zhang, Lucas Maes, Alan Milligan et al.
Understanding and Enhancing Mask-Based Pretraining towards Universal Representations
Mingze Dong, Leda Wang, Yuval Kluger
Understanding and Enhancing Message Passing on Heterophilic Graphs via Compatibility Matrix
Zhuonan Zheng, Yuanchen Bei, Zhiyao Zhou et al.
Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron
Yiran Zhao, Wenxuan Zhang, Yuxi Xie et al.
Understanding and Enhancing the Transferability of Jailbreaking Attacks
Runqi Lin, Bo Han, Fengwang Li et al.
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
Weixin Chen, Han Zhao
Understanding and Improving Fast Adversarial Training against $l_0$ Bounded Perturbations
Xuyang Zhong, Yixiao Huang, Chen Liu
Understanding and Improving Length Generalization in Recurrent Models
Ricardo Buitrago Ruiz, Albert Gu
Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing
Peihao Wang, Ruisi Cai, Yuehao Wang et al.
Understanding and Mitigating Hallucination in Large Vision-Language Models via Modular Attribution and Intervention
Tianyun Yang, Ziniu Li, Juan Cao et al.
Understanding and Mitigating Memorization in Diffusion Models for Tabular Data
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen et al.
Understanding and Mitigating Memorization in Generative Models via Sharpness of Probability Landscapes
Dongjae Jeon, Dueun Kim, Albert No