Open Source
Open-source initiatives are democratizing access to and accelerating advancements in various scientific and technological fields by fostering collaboration and reproducibility. Current research focuses on developing open-source tools and datasets across diverse domains, including AI models (like LLMs and specialized models for tasks such as medical diagnosis or autonomous driving), simulation environments for robotics and network analysis, and benchmarks for evaluating model performance. This open approach significantly benefits the scientific community by enabling wider participation, facilitating rigorous validation, and accelerating the translation of research into practical applications across numerous sectors.
Papers
OmniEvent: A Comprehensive, Fair, and Easy-to-Use Toolkit for Event Understanding
Hao Peng, Xiaozhi Wang, Feng Yao, Zimu Wang, Chuzhao Zhu, Kaisheng Zeng, Lei Hou, Juanzi Li
Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data
Yifan Peng, Jinchuan Tian, Brian Yan, Dan Berrebbi, Xuankai Chang, Xinjian Li, Jiatong Shi, Siddhant Arora, William Chen, Roshan Sharma, Wangyou Zhang, Yui Sudo, Muhammad Shakeel, Jee-weon Jung, Soumi Maiti, Shinji Watanabe