activity
20232026
most citedFederated Multi-Task Learning on Non-IID Data Silos: An Experimental Study

2 citations · 4 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CV2026

HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling

Mei Li, Huayi Zhou, Suizhi Huang +3

Regressing 3D rotations of objects from 2D images is a crucial yet challenging task, with broad applications in autonomous driving, virtual reality, and robotic control. Existing r…

cs.LG2026

TextResNet: Decoupling and Routing Optimization Signals in Compound AI Systems via Deep Residual Tuning

Suizhi Huang, Mei Li, Han Yu +1

Textual Gradient-style optimizers (TextGrad) enable gradient-like feedback propagation through compound AI systems. However, they do not work well for deep chains. The root cause o…

eess.IV20251 cited

MORE: Multi-Organ Medical Image REconstruction Dataset

Shaokai Wu, Yapan Guo, Yanbiao Ji +6

CT reconstruction provides radiologists with images for diagnosis and treatment, yet current deep learning methods are typically limited to specific anatomies and datasets, hinderi…

cs.SE20251 cited

A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System

Jiale Guo, Suizhi Huang, Mei Li +8

The integration of Large Language Models (LLMs) into software engineering has driven a transition from traditional rule-based systems to autonomous agentic systems capable of solvi…

cs.LG2025

BECAME: BayEsian Continual Learning with Adaptive Model MErging

Mei Li, Yuxiang Lu, Qinyan Dai +3

Continual Learning (CL) strives to learn incrementally across tasks while mitigating catastrophic forgetting. A key challenge in CL is balancing stability (retaining prior knowledg…

cs.CV2025

Few-shot Implicit Function Generation via Equivariance

Suizhi Huang, Xingyi Yang, Hongtao Lu +1

Implicit Neural Representations (INRs) have emerged as a powerful framework for representing continuous signals. However, generating diverse INR weights remains challenging due to…