✨MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model

📝 Summary:
MarS is a financial market simulation engine using LMM, an order-level generative model. It creates realistic, interactive market scenarios for risk-free strategy training and analysis. This offers scalability and strong realism.

🔹 Publication Date: Published on Sep 4, 2024

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2409.07486
• PDF: https://arxiv.org/pdf/2409.07486
• Github: https://github.com/microsoft/mars

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#FinancialMarkets #GenerativeAI #Simulation #LLM #FinTech

✨FinTRec: Transformer Based Unified Contextual Ads Targeting and Personalization for Financial Applications

📝 Summary:
FinTRec is a transformer-based framework for financial recommendation systems. It handles complex user interactions and multiple products, outperforming traditional tree models. This unified approach improves performance and reduces costs.

🔹 Publication Date: Published on Nov 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14865
• PDF: https://arxiv.org/pdf/2511.14865

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#FinTech #RecommendationSystems #Transformers #AI #MachineLearning

✨AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets

📝 Summary:
AI-Trader introduces the first fully automated live benchmark for evaluating LLM agents in financial decision-making. It reveals that general AI does not ensure trading success, with most agents showing poor returns and weak risk management. Risk control proves crucial, and liquid markets offer b...

🔹 Publication Date: Published on Dec 1, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10971
• PDF: https://arxiv.org/pdf/2512.10971
• Project Page: https://ai4trade.ai/
• Github: https://github.com/HKUDS/AI-Trader

✨ Datasets citing this paper:
• https://huggingface.co/datasets/T1anyu/AI-Trader

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#AI #LLMAgents #FinTech #AlgorithmicTrading #FinancialAI

✨τ-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge

📝 Summary:
τ-Knowledge extends τ-Bench to evaluate conversational agents in fintech customer support, integrating external knowledge with tool use. Its τ-Banking domain involves navigating 700 documents and executing tool-mediated updates. Frontier models achieve only ~25.5% pass, struggling with document r...

🔹 Publication Date: Published on Mar 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.04370
• PDF: https://arxiv.org/pdf/2603.04370

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#ConversationalAI #Fintech #LLMEvaluation #KnowledgeIntegration #ToolUse

✨QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

📝 Summary:
QuantAgent is a multi-agent LLM framework for high-frequency trading. It uses specialized agents for indicators, patterns, trends, and risk to make rapid decisions. It outperforms existing neural and rule-based systems in accuracy and returns.

🔹 Publication Date: Published on Sep 12, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09995
• PDF: https://arxiv.org/pdf/2509.09995
• Project Page: https://Y-Research-SBU.github.io/QuantAgent/
• Github: https://github.com/Y-Research-SBU/QuantAgent

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#LLM #MultiAgent #HighFrequencyTrading #FinTech #AlgorithmicTrading

✨Type-Checked Compliance: Deterministic Guardrails for Agentic Financial Systems Using Lean 4 Theorem Proving

📝 Summary:
The Lean-Agent Protocol ensures deterministic regulatory compliance for financial AI. It uses Lean 4 theorem proving to auto-formalize policies, verifying agent actions as mathematical conjectures for cryptographic-level certainty, addressing LLM probabilistic nature.

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01483
• PDF: https://arxiv.org/pdf/2604.01483
• Project Page: https://axiom.devrashie.space
• Github: https://github.com/arkanemystic/lean-agent-protocol

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#FormalVerification #AICompliance #FinTech #Lean4 #LLMAgents