Papers
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
Chenghan Xie, Chenxi Li, Chuwen Zhang et al.
Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning
Zhongzhi Chen, Xingwu Sun, Xianfeng Jiao et al.
T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Large Language Model Signals for Science Question Answering
Lei Wang, Yi Hu, Jiabang He et al.
TTTS: Tree Test Time Simulation for Enhancing Decision Tree Robustness against Adversarial Examples
Seffi Cohen, Ofir Arbili, Yisroel Mirsky et al.
Tuning-Free Inversion-Enhanced Control for Consistent Image Editing
Xiaoyue Duan, Shuhao Cui, Guoliang Kang et al.
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients
Mengdi Wang, Anna Bodonhelyi, Efe Bozkir et al.
Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative Data
Yiwei Li, Peiwen Yuan, Shaoxiong Feng et al.
Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks
Xin Ding, Yongwei Wang, Zuheng Xu
Twice Class Bias Correction for Imbalanced Semi-supervised Learning
Lan Li, Bowen Tao, Lu Han et al.
Two-Stage Evolutionary Reinforcement Learning for Enhancing Exploration and Exploitation
Qingling Zhu, Xiaoqiang Wu, Qiuzhen Lin et al.
UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation
Kefu Yi, Kai Luo, Xiaolei Luo et al.
UFDA: Universal Federated Domain Adaptation with Practical Assumptions
Xinhui Liu, Zhenghao Chen, Luping Zhou et al.
UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation
Yue Zhao, Congyi Li, Kai Chen
UMIE: Unified Multimodal Information Extraction with Instruction Tuning
Lin Sun, Kai Zhang, Qingyuan Li et al.
U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
Xiang Ma, Xuemei Li, Lexin Fang et al.
Uncertainty-Aware Yield Prediction with Multimodal Molecular Features
Jiayuan Chen, Kehan Guo, Zhen Liu et al.
Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation
Hui Chen, Yinxu Jia, Guanghui Wang et al.
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
Tailin Wu, Willie Neiswanger, Hongtao Zheng et al.
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model
Shunsuke Horii, Yoichi Chikahara
Uncertainty Regularized Evidential Regression
Kai Ye, Tiejin Chen, Hua Wei et al.
Uncovering and Mitigating the Hidden Chasm: A Study on the Text-Text Domain Gap in Euphemism Identification
Yuxue Hu, Junsong Li, Mingmin Wu et al.
Understanding and Improving Optimization in Predictive Coding Networks
Nicholas Alonso, Jeffrey Krichmar, Emre Neftci
Understanding and Leveraging the Learning Phases of Neural Networks
Johannes Schneider, Mohit Prabhushankar