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AntTech
AntTech
Dec 6, 2025 · Artificial Intelligence

FinEval‑KR: Diagnosing Knowledge vs. Reasoning Gaps in Financial Large Language Models

FinEval‑KR, a new EMNLP2025 evaluation framework co‑authored by Shanghai University of Finance and Economics and Ant Group, separates knowledge coverage from logical reasoning to reveal why financial LLMs often hallucinate on calculation tasks, introduces KS, RS, and CS metrics, and ranks 18 state‑of‑the‑art models on a rigorously curated finance dataset.

Knowledge vs reasoningLLM evaluationfinance AI
0 likes · 14 min read
FinEval‑KR: Diagnosing Knowledge vs. Reasoning Gaps in Financial Large Language Models
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Sep 21, 2025 · Artificial Intelligence

FinKario: Event‑Enhanced Financial Knowledge Graphs Boost A‑Share Sharpe Ratio to 4.9

This article reviews the FinKario paper, which introduces an event‑augmented financial knowledge graph and a two‑stage RAG retrieval strategy that together enable real‑time knowledge updates and efficient integration of long‑form research reports, yielding a Sharpe ratio of 4.9 and outperforming baseline LLMs and institutional strategies in back‑testing.

FinKarioLLMRAG
0 likes · 10 min read
FinKario: Event‑Enhanced Financial Knowledge Graphs Boost A‑Share Sharpe Ratio to 4.9
AntTech
AntTech
Sep 6, 2024 · Artificial Intelligence

Large Model Industry Trustworthy Application Framework Research Report

Ant Group and the China Academy of Information and Communications Technology released a research report outlining a trustworthy application framework for large models in rigorous sectors such as finance and healthcare, detailing technical safeguards, industry case studies, and guidance for scalable, secure AI deployment.

AI GovernanceAI deploymentHealthcare AI
0 likes · 3 min read
Large Model Industry Trustworthy Application Framework Research Report
Data Thinking Notes
Data Thinking Notes
Apr 11, 2024 · Artificial Intelligence

How Financial Institutions Are Building Their Own Large Language Models

This article explores how the finance sector is creating specialized large language models—covering the shift from generic to domain‑specific models, training innovations, evaluation methods, and real‑world applications such as marketing, customer service, risk control, and operational analytics.

ApplicationsLarge Language ModelsModel Training
0 likes · 16 min read
How Financial Institutions Are Building Their Own Large Language Models