F²Agent融合多模态金融数据与智能体推理，为交易决策带来全新范式。
arXiv:2608.05668v1 Announce Type: cross Abstract: With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal d…
用有限预算自适应训练风险敏感的Q学习，兼顾收益与尾部风险，金融决策新解法。
arXiv:2608.04305v1 Announce Type: new Abstract: Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objective…
金融领域首个评估大模型工具调用能力的基准，看智能体能否玩转真实金融工具
arXiv:2603.08262v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) into the financial domain is driving a paradigm sh…
用大模型拆分并执行机构级父订单，实测其在交易调度与指令执行上的边界，金融自动化新看点。
arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large …
从“看似合理”到“银行级可靠”，CM-LRS框架用七大维度量化评估大模型输出，为资本市场的AI应用提供可信标尺。
arXiv:2607.21340v1 Announce Type: new Abstract: In capital-markets workflows the question is rarely whether a large language model can produce a fluen…
一份来自佐治亚理工的硕士研究，系统评估大语言模型在技术市场分析中的表现，揭示AI交易潜力。
arXiv:2607.15414v1 Announce Type: cross Abstract: Large Language Models (LLMs) have emerged as powerful tools for processing the heterogeneous informa…
金融大模型评测迎来新范式，元基准如何精准捕捉行业认知需求？
arXiv:2607.01740v1 Announce Type: new Abstract: Public LLM leaderboards optimise for global average performance and do not capture the specific cognit…
金融表格数据生成的约束扩散新方法，兼顾真实性与业务规则，ICAIF 2025前沿研究。
arXiv:2606.28674v1 Announce Type: new Abstract: Generative models in finance face the dual challenge of producing realistic data while satisfying stri…
首个专为SEC财务文件解析设计的LLM评测基准，填补金融AI真实场景评估空白
arXiv:2602.07294v4 Announce Type: replace-cross Abstract: With the increasing deployment of Large Language Models (LLMs) in the finance domain, LLMs a…
大模型交易代理会“预判”崩盘？研究发现失败前有独特信号模式，如规划嵌入漂移和有效秩收缩。
arXiv:2605.28850v1 Announce Type: new Abstract: We study behavioral alignment and representation dynamics of large language model (LLM) agents in fina…
相关性感知的全流程基准测试，专为评估LLM投资组合管理能力而设计，填补金融AI评估空白
arXiv:2605.27887v1 Announce Type: new Abstract: LLMs have shown strong performance across diverse financial tasks, yet portfolio management (PM), a cr…
首个针对量化回测的LLM基准测试，被KDD 2026录用，评估自动策略生成能力。
arXiv:2605.17937v1 Announce Type: new Abstract: Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high t…
探讨大语言模型能否作为信用风险模型的事后可解释工具，前沿研究视角值得关注。
arXiv:2602.18895v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promise in translating model-based explanations into…