Final-year B.Eng. student in Electrical and Computer Engineering (Computer Engineering stream) at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), and undergraduate researcher in the Network and Artificial Intelligence System (NAIS) Lab, advised by Prof. Fangxin Wang.
Major GPA 3.90/4.00 (3/60, top 5% in the Computer Engineering stream) · Dean's List 2023–24, 2024–25, 2025–26
- 🌐 Homepage: sv-arcode.github.io
- 📄 CV: Download PDF
- 📫 Email:
123090028@link.cuhk.edu.cn
Multimodal large language models · hidden-intent & emotion understanding · multimodal reasoning · model interpretability
- MISID — Hidden-Intent Recognition in Strategic Deception Games Multimodal, multi-turn benchmark with 3,962 temporally aligned audiovisual segments and a two-tier annotation scheme. Designed FRACTAM's modal decoupling and text reconstruction component, independently handled the inter-annotator agreement study, and contributed to evaluation, ablation studies, and the LLM-as-a-Judge protocol. Co-first author — submitted to AAAI 2027 (under review).
- AffectiveArt Challenge 2026 — ACM Multimedia Grand Challenge, Track 2 Led a 3-member team; designed the overall architecture; fine-tuned Gemma, Qwen, SigLIP2, and DINOv3 classifiers; and designed and implemented validation-weighted voting that outperformed the best individual model. Independently fine-tuned SigLIP2 and DINOv3 for visual-attribute salience prediction; salience and classification outputs conditioned a LoRA-fine-tuned Qwen3.5-27B description model. Rank 5 / 14 on the official leaderboard (overall score 0.8236).
- Butterfly-CNN-Interpretability — repo 4-layer CNN classifying 10 visually similar butterfly species (83.23% test accuracy), with Class Activation Mapping implemented from scratch and PCA feature-space visualization. ECE4513 Image Processing and Computer Vision final project.
- Preparing PhD applications (Fall 2027) — multimodal reasoning & social intelligence
- MISID is under review at AAAI 2027