5 papers
ReCalMatch:Reliability-Calibrated Semantic Guidance for Semi-Supervised Fine-Grained Recognition
Yundi Hong, Hongyang He, Zheng Fang +2
Semi-supervised fine-grained visual recognition is highly vulnerable to overconfident pseudo-label errors: visually similar categories frequently produce high-confidence yet incorr…
Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation
Xuanyu Liu, Zheng Fang, Hongyang He +2
Semi-supervised adaptation of vision foundation models (VFMs) commonly freezes the pretrained backbone and updates lightweight modules such as LoRA. However, pseudo-labels have mix…
Revisiting Chain-of-Thought Reasoning under Limited Supervision: Semi-supervised Chain-of-Thought Learning
Hongyang He, Jiuming Liu, Victor Sanchez
Chain-of-thought (CoT) reasoning has emerged as an effective approach for activating latent reasoning capabilities in large language models. However, most existing CoT methods use…
Semi-Supervised Vision-Language-Action Model
Hongyang He, Jiuming Liu, Victor Sanchez
Vision-Language-Action (VLA) models enable robots to predict actions directly from visual observations and language instructions, but adapting them to new environments still depend…
TAPM-Net: Trajectory-Aware Perturbation Modeling for Infrared Small Target Detection
Hongyang Xie, Hongyang He, Victor Sanchez
Infrared small target detection (ISTD) remains a long-standing challenge due to weak signal contrast, limited spatial extent, and cluttered backgrounds. Despite performance improve…