thuiar/OKD-Reading-List
Papers for Open Knowledge Discovery
This is a curated collection of academic papers focused on identifying and handling "open knowledge" in AI systems. It provides researchers and practitioners with a resource to understand how to detect new user intents in conversational AI or recognize new categories in image processing. The list is organized by NLP, Computer Vision, and Machine Learning domains, with papers on tasks like out-of-domain detection and new category discovery.
120 stars. No commits in the last 6 months.
Use this if you are an AI researcher or machine learning engineer looking for academic literature on how to detect and manage unexpected or unknown data inputs in your models, especially for natural language processing or computer vision tasks.
Not ideal if you are looking for ready-to-use code, datasets, or a tutorial for implementing open knowledge discovery in a specific application.
Stars
120
Forks
24
Language
TeX
License
BSD-3-Clause
Category
Last pushed
Dec 21, 2023
Commits (30d)
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