Shuai Li

An efficient joint evolutionary algorithm-based neural network model for air quality prediction

Peiyang Wei, Mingsheng Shang, Xi Chen, Yuyan Wang, Jianhong Gan, Shuai Li

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias

Zixiang Xu, Sixian Li, Huaxing Liu, Xiang Wang, Shuai Li, Zirui Song, et al.

Existing studies of LLM-as-judge scoring bias work predominantly at the input-output level: they perturb inputs, measure score deltas, and propose prompt-level mitigations. We argue that the same biases admit a representation-level account in the judge's hidden state, complementa…Read more

Learning Probabilistic Embeddings for Unsupervised Action Segmentation

Shuai Li, Duc Manh Vu, Juergen Gall

This paper concerns the problem of unsupervised temporal action segmentation for long, untrimmed videos. Recent successful approaches follow a joint representation learning and clustering paradigm, where optimal transport (OT) is adopted to produce pseudo labels for learning fram…Read more

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity

Shuai Li, Qinglin Wang, Ping Luo, Jiahuan Wang, Hongyang Hu, Haotian Mo, et al.

Federated Transformer training increasingly relies on local AdamW, whose adaptive updates can provide much stronger local progress than SGD-based training. However, under heterogeneous client data, even globally corrected AdamW updates may remain highly uneven in coordinate-wise…Read more

HiReFF: High-Resolution Feedforward Human Reconstruction from Uncalibrated Sparse-View Video

Yiming Jiang, Hanzhang Tu, Wenfeng Song, Siyou Lin, Liang An, Shuai Li, et al.

Uncalibrated volumetric video streaming for human reconstruction is essential for holographic communication and AR/VR, yet remains challenging due to the need for temporal consistency and computational efficiency from sparse-view inputs. Existing methods rely on per-scene optimiz…Read more

Kriging and neural network models for pressure losses across perforated plates

Shuai Li

In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates with circular perforations in turbulent flows. The models are developed using two sets of experimental data available in the lite…Read more

MindFlow: Harmonizing Cognitive Semantics and Acoustic Dynamics for Facial Animation Generation in Dyadic Conversations

Hejia Chen, Haoxian Zhang, Xu He, Xiaoqiang Liu, Pengfei Wan, Shoulong Zhang, et al.

Generating lifelike facial animation for dyadic conversations requires reconciling high-level cognitive intent with precise low-level motor reflexes, yet existing methods fall short in the semantic understanding of dialogue context and in precise dynamic control. In this paper, w…Read more

A Novel Dual-Modality Dual-View Hybrid Deep Learning–Machine Learning Framework for the Prediction of Carotid Plaque Vulnerability via Late Fusion

Wenxuan Zhang, Chao Hou, Xinyi Wang, Hongyu Kang, Shuai Li, Yu Sun, et al.

Background: Ultrasound imaging is an ideal tool for regular carotid plaque screening to identify individuals at high risk of stroke for clinical intervention. However, no existing study leverages multi-modal multi-view ultrasound imaging for AI-enabled auto-classification of caro…Read more