Wang Ranran — accepted AI-conference papers

2026

MarketSim: Simulating Stock Markets with Large-Scale Generative Agents

Jinghua Piao, zhentao liu, Cheng Huang, Huang Jiarui, Songwei Li, Wang Ranran +1

ICML 2026poster

Stock markets are one of the most complex systems in the modern world, where prices emerge from billions of decentralized interactions among heterogeneous participants in an ever-evolving information landscape. While high-fidelity simulation is important for understanding market dynamics, existing a…

Cited by 0 Source ↗Scholar ↗

2026

Towards Professional-Grade Financial Agents: Benchmarking, Tooling, and Structured Reasoning

Cheng Huang, Jinghua Piao, Wang Ranran, Yong Li

ICML 2026poster

Financial reasoning requires precise execution. While Large Language Model (LLM) agents have shown encouraging progress in financial reasoning, their effectiveness in realistic financial workflows is severely hindered by the lack of holistic benchmarks and the fragility of unstructured reasoning. To…

Cited by 0 Source ↗Scholar ↗