Feb. 15, 2024, 5:45 a.m. | Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning

cs.CL updates on arXiv.org arxiv.org

arXiv:2402.08831v1 Announce Type: new
Abstract: With tremendous efforts on developing effective e-commerce models, conventional e-commerce models show limited success in generalist e-commerce modeling, and suffer from unsatisfactory performance on new users and new products - a typical out-of-domain generalization challenge. Meanwhile, large language models (LLMs) demonstrate outstanding performance in generalist modeling and out-of-domain generalizability in many fields. Toward fully unleashing their power for e-commerce, in this paper, we construct ECInstruct, the first open-sourced, large-scale, and high-quality benchmark instruction dataset for …

arxiv commerce cs.ai cs.cl cs.ir data e-commerce language language models large language large language models quality scale type

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Senior DevOps Engineer- Autonomous Database

@ Oracle | Reston, VA, United States