What is the most surprising finding in your research?
Fast access to some projects
Source codes of all my works will be shared on GitHub, and the trained models and datasets will be released on 🤗 Hugging Face.
Boston University:
- 🔥 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤 𝐃𝐚𝐭𝐚𝐬𝐞𝐭 - GSM8K-Consistency Benchmark (available on 🤗 Hugging Face, still under preparation)
- 🔨 𝐓𝐨𝐨𝐥𝐤𝐢𝐭 - PromptCraft: A Prompt Perturbation Toolkit and the released PyPI Package
- 📚 𝐏𝐚𝐩𝐞𝐫 𝐒𝐮𝐫𝐯𝐞𝐲 - Awesome LLM Self-Consistency
- 📚 𝐏𝐚𝐩𝐞𝐫 𝐒𝐮𝐫𝐯𝐞𝐲 - Awesome Semantic Textual Similarity (STS)
City University of Hong Kong:
- Non-local Modeling for Image Quality Assessment
- Context-aware Non-local Compensation for Image Quality Assessment
Northeast Electric Power University:
- 🔥 𝐋𝐢𝐛𝐫𝐚𝐫𝐲 - EEG Deep Learning Library
- EEG Motor Imagery Signals Classification via CNN
- Sonar Image Segmentation via Entropy Method
Philips Research:
- Medical Named Entity Recognition
- Medical Concept Mapping
- Deploy PyTorch NER Model with Flask and Docker as Web App
- Dynamic Webs Crawlering in Python
Others: