About
I am currently a Master's student in AI at CUC, with research experience at Microsoft Research Asia and Meituan. My focus lies in LLM Agents, Post-training, and Reasoning. I have published papers at top conferences like KDD and built complex multi-agent systems for game generation. I aim to bridge the gap between cutting-edge AI research and real-world applications.
Work Experience
Check out my latest work
My Research Contributions
My research focuses on Large Language Models, Multi-Agent Systems, and Temporal Knowledge Graphs. Here are my recent publications at top-tier conferences and journals.
Fine-tuning Multimodal Large Language Models for Product Bundling
KDD Conference
Proposed the Bundle-MLLM framework, utilizing hybrid multimodal tokens and Bundle Prompting for Product Bundling tasks. Achieved 6.4 percent to 11.2 percent SOTA improvement across four real-world datasets.
Integrate Temporal Graph Learning into LLM-based Temporal Knowledge Graph Model
Research Paper
Introduced TGL-LLM to bridge the gap in temporal modeling for LLMs by aligning graph embeddings with LLM token embeddings. Achieved up to 15 percent Acc at 4 improvement on the POLECAT dataset.
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting
Research Paper
Systematically evaluated mainstream LLMs like GPT-3.5-turbo and Llama 2 on temporal event forecasting tasks. Constructed the high-quality multimodal dataset MidEast-TE-mini.
Get in Touch
Open to new opportunities? I'm always ready to discuss AI research and engineering. Feel free to send me an email directly, and I'll respond as soon as possible.