1 citations · 2 across the 4 of their papers we have counts for
4 papers
ACA-Net: Future Graph Learning for Logistical Demand-Supply Forecasting
Jiacheng Shi, Haibin Wei, Jiang Wang +3
Logistical demand-supply forecasting that evaluates the alignment between projected supply and anticipated demand, is essential for the efficiency and quality of on-demand food del…
ShoppingBench: A Real-World Intent-Grounded Shopping Benchmark for LLM-based Agents
Jiangyuan Wang, Kejun Xiao, Qi Sun +4
Existing benchmarks in e-commerce primarily focus on basic user intents, such as finding or purchasing products. However, real-world users often pursue more complex goals, such as…
MindSpeed RL: Distributed Dataflow for Scalable and Efficient RL Training on Ascend NPU Cluster
Laingjun Feng, Chenyi Pan, Xinjie Guo +11
Reinforcement learning (RL) is a paradigm increasingly used to align large language models. Popular RL algorithms utilize multiple workers and can be modeled as a graph, where each…
STTM: A New Approach Based Spatial-Temporal Transformer And Memory Network For Real-time Pressure Signal In On-demand Food Delivery
Jiang Wang, Haibin Wei, Xiaowei Xu +4
On-demand Food Delivery (OFD) services have become very common around the world. For example, on the Ele.me platform, users place more than 15 million food orders every day. Predic…