F$^2$Agent: Financial Fusion of Agentic Intelligence for Multimodal Trading
With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial trading. Although recent advancements in Large Language Model (LLM)-based agents have enabled the ingestion of multimodal inputs, existing methods fail to capture nuanced cross-modal dependencies and remain vulnerable to market noise, due to limited multimodal modeling, ineffective fusion mechanisms, and inadequate robustness. To address these challenges, we propose F$^2$Agent, a novel multimodal agentic paradigm driven by the Financial Fusion of Agentic Intelligence. F$^2$Agent first deploys a hierarchy of specialized agents to comprehensi...
| Authors | Changshuo Liu, Yanzheng Jin, Shangfeng Cai et al. |
|---|---|
| Primary category | cs.MA |
| Published | 6 August 2026 |
| Last updated at source | 6 August 2026 |
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