1 code implementation • 22 May 2024 • Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Minsoo Kang, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff Schneider, Eduard Hovy, Roger Grosse, Eric Xing
Large language models (LLMs) are trained on a vast amount of human-written data, but data providers often remain uncredited.
1 code implementation • 22 Apr 2024 • Xiaochen Kev Gao, Feng Yao, Kewen Zhao, Beilei He, Animesh Kumar, Vish Krishnan, Jingbo Shang
In this paper, we delve into the patent approval pre-diction task and unveil that simple domain-specific graph methods outperform enlarging the model, using the intrinsic dependencies within the patent data.
1 code implementation • 24 May 2022 • Zihan Wang, Kewen Zhao, Zilong Wang, Jingbo Shang
Fine-tuning pre-trained language models has recently become a common practice in building NLP models for various tasks, especially few-shot tasks.