3 citations · 3 across the 11 of their papers we have counts for
13 papers
Are Large Language Models Reliable Reviewers? A Benchmark for Error Detection in Financial Documents
Ying He, Zhouhong Gu, Zhecheng Hu +8
Ensuring the accuracy of financial documents is critical for economic analysis, regulatory compliance, and corporate decision-making. Several studies have shown that Large Language…
Sharper Analysis of Single-Loop Methods for Bilevel Optimization
Yubo Zhou, Jun Shu, Luo Luo +4
Bilevel optimization underpins many machine learning applications, including hyperparameter optimization, meta-learning, neural architecture search, and reinforcement learning. Whi…
Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation
Yubo Zhou, Jianghao Wu, Ping Ye +2
Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medical imaging due to the domain g…
Understanding the Generalization of Bilevel Programming in Hyperparameter Optimization: A Tale of Bias-Variance Decomposition
Yubo Zhou, Jun Shu, Junmin Liu +1
Gradient-based hyperparameter optimization (HPO) have emerged recently, leveraging bilevel programming techniques to optimize hyperparameter by estimating hypergradient w.r.t. vali…
A3-TTA: Adaptive Anchor Alignment Test-Time Adaptation for Image Segmentation
Jianghao Wu, Xiangde Luo, Yubo Zhou +3
Test-Time Adaptation (TTA) offers a practical solution for deploying image segmentation models under domain shift without accessing source data or retraining. Among existing TTA st…
On the Convergence of Single-Loop Stochastic Bilevel Optimization with Approximate Implicit Differentiation
Yubo Zhou, Luo Luo, Guang Dai +1
Stochastic Bilevel Optimization has emerged as a fundamental framework for meta-learning and hyperparameter optimization. Despite the practical prevalence of single-loop algorithms…
Rethinking Message Passing Neural Networks with Diffusion Distance-guided Stress Majorization
Haoran Zheng, Renchi Yang, Yubo Zhou +1
Message passing neural networks (MPNNs) have emerged as go-to models for learning on graph-structured data in the past decade. Despite their effectiveness, most of such models stil…
Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization
Chengli Tan, Yubo Zhou, Haishan Ye +7
Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many studies suggest that they are prone…
Advancing Music Therapy: Integrating Eastern Five-Element Music Theory and Western Techniques with AI in the Novel Five-Element Harmony System
Yubo Zhou, Weizhen Bian, Kaitai Zhang +1
In traditional medical practices, music therapy has proven effective in treating various psychological and physiological ailments. Particularly in Eastern traditions, the Five Elem…
EmoSpeech: A Corpus of Emotionally Rich and Contextually Detailed Speech Annotations
Weizhen Bian, Yubo Zhou, Kaitai Zhang +1
Advances in text-to-speech (TTS) technology have significantly improved the quality of generated speech, closely matching the timbre and intonation of the target speaker. However,…
CogSimulator: A Model for Simulating User Cognition & Behavior with Minimal Data for Tailored Cognitive Enhancement
Weizhen Bian, Yubo Zhou, Yuanhang Luo +6
The interplay between cognition and gaming, notably through educational games enhancing cognitive skills, has garnered significant attention in recent years. This research introduc…
IntellectSeeker: A Personalized Literature Management System with the Probabilistic Model and Large Language Model
Weizhen Bian, Siyan Liu, Yubo Zhou +4
Faced with the burgeoning volume of academic literature, researchers often need help with uncertain article quality and mismatches in term searches using traditional academic engin…
Embedded Collaborative Filtering for "Cold Start" Prediction
Yubo Zhou, Ali Nadaf
Using only implicit data, many recommender systems fail in general to provide a precise set of recommendations to users with limited interaction history. This issue is regarded as…