TimeHF 2.0: Multimodal, Multivariate, and Multi-Region Collaborative Forecasting for Large-Scale Retail Supply Chains
arXiv cs.AI · Zhongxuan Han, Zhengxin Shi, Kunxiu Chen, Xiaolin Huang, Yulin Huang, Anni Zhang, Xiaoming Lin, Zhengyu Chen, Xue Yu, Yang Liu, Yuanyuan Yang, Yangyang Zhang, Junheng Huang, Dongyang Geng, Ben Zhang, ·
arXiv:2611.10521v1 Announce Type: new Abstract: Large-scale retail supply chains need sales forecasts for specified products, future dates or planning windows, and regions under the conditions available at the forecast origin. Regional sparsity, changing environments, volatile sales, and unfamiliar business…
Excerpt provided by arXiv cs.AI via its public feed. Full reporting belongs to the original publisher.
Read the full story on arXiv cs.AI
Related coverage
TechCrunch AI · 14m ago
OpenAI rolls out new business profiles, making ChatGPT just a little bit more like Google
AWS Machine Learning · 53m ago
Autonomous treasury agents: How Trovata built an AI-native solution on Amazon Bedrock and AgentCore
The Verge AI · 1h ago
ChatGPT is getting verified AI ‘Business Agents’
The Verge AI · 1h ago
Anthropic has its own AI-powered office suite now