103 citations · 310 across the 23 of their papers we have counts for
8 papers · 1 filter
PyPose v0.6: The Imperative Programming Interface for Robotics
Zitong Zhan, Xiangfu Li, Qihang Li +33
PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has…
Randomized algorithms for precise measurement of differentially-private, personalized recommendations
Allegra Laro, Yanqing Chen, Hao He +1
Personalized recommendations form an important part of today's internet ecosystem, helping artists and creators to reach interested users, and helping users to discover new and eng…
SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark
Liang Xu, Anqi Li, Lei Zhu +7
Large language models (LLMs) have shown the potential to be integrated into human daily lives. Therefore, user preference is the most critical criterion for assessing LLMs' perform…
Taxonomy-Structured Domain Adaptation
Tianyi Liu, Zihao Xu, Hao He +3
Domain adaptation aims to mitigate distribution shifts among different domains. However, traditional formulations are mostly limited to categorical domains, greatly simplifying nua…
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
Yixun Liang, Hao He, Ying-cong Chen
Generalizable neural surface reconstruction techniques have attracted great attention in recent years. However, they encounter limitations of low confidence depth distribution and…
Weakly Supervised AUC Optimization: A Unified Partial AUC Approach
Zheng Xie, Yu Liu, Hao-Yuan He +2
Since acquiring perfect supervision is usually difficult, real-world machine learning tasks often confront inaccurate, incomplete, or inexact supervision, collectively referred to…
Label Name is Mantra: Unifying Point Cloud Segmentation across Heterogeneous Datasets
Yixun Liang, Hao He, Shishi Xiao +2
Point cloud segmentation is a fundamental task in 3D vision that serves a wide range of applications. Although great progresses have been made these years, its practical usability…
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
Jierun Chen, Shiu-hong Kao, Hao He +4
To design fast neural networks, many works have been focusing on reducing the number of floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does no…