activity
20242026
most citedBetter Sampling, towards Better End-to-end Small Object Detection

2 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

From Trace to Fix: Residual Task State in Long-Horizon Agents

Zile Huang, Ser-nam Lim

Recovering from failures in long-horizon, stateful language agents is challenging because the action introducing a defect, the symptom exposing it, and the persistent state requiri…

cs.CV2026

Functional Cross-layer Experts Routing for One-step Diffusion Distillation

Zile Huang, Ser-nam Lim

One-step distillation compresses diffusion trajectories into a single forward evaluation, yet how internal capacity should be structured within that remaining pass remains largely…

cs.CV2025

AlignVid: Training-Free Attention Scaling for Semantic Fidelity in Text-Guided Image-to-Video Generation

Yexin Liu, Wen-Jie Shu, Zile Huang +6

Text-guided image-to-video generation has made substantial progress, yet it still struggles to execute text-specified edits that require substantial changes to a reference image (\…

cs.CV2025

Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis

Chengzhi Liu, Zile Huang, Zhe Chen +6

Ophthalmologists typically require multimodal data sources to improve diagnostic accuracy in clinical decisions. However, due to medical device shortages, low-quality data and data…

cs.CV2024★ 2 cited

Better Sampling, towards Better End-to-end Small Object Detection

Zile Huang, Chong Zhang, Mingyu Jin +3

While deep learning-based general object detection has made significant strides in recent years, the effectiveness and efficiency of small object detection remain unsatisfactory. T…

cs.CV2024★ 1 cited

MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural Network

Chengzhi Liu, Zheng Tao, Zihong Luo +1

Time series analysis and modelling constitute a crucial research area. Traditional artificial neural networks struggle with complex, non-stationary time series data due to high com…