4 papers
DScheLLM: Enabling Dynamic Scheduling through a Fine-Tuned Dual-System Large language Model
Lixiang Zhang, Chenggong Zhao, Qing Gao +3
Production scheduling is highly susceptible to dynamic disruptions, such as variations in processing times, machine availability, and unexpected task insertions. Conventional appro…
Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
Yanjun Zheng, Xiyang Du, Longfei Liao +10
Large Language Models (LLMs) exhibit considerable promise in financial applications; however, prevailing models frequently demonstrate limitations when confronted with scenarios th…
Agentar-DeepFinance-100K: A Large-Scale Financial Dataset via Systematic Chain-of-Thought Synthesis Optimization
Xiaoke Zhao, Zhaowen Zhou, Lin Chen +12
Recent advancements in large language models (LLMs) have demonstrated remarkable general reasoning capabilities, holding significant potential for applications in the financial dom…
I Can Tell Your Secrets: Inferring Privacy Attributes from Mini-app Interaction History in Super-apps
Yifeng Cai, Ziqi Zhang, Mengyu Yao +8
Super-apps have emerged as comprehensive platforms integrating various mini-apps to provide diverse services. While super-apps offer convenience and enriched functionality, they ca…