A new framework called the Knowledge-Driven Analytics Framework (KDAF) has been proposed for enhancing the trustworthiness of Large Language Models (LLMs) in enterprise finance. This framework focuses on auditability and traceability of information, which are critical for regulated financial workflows. Evaluations show that while KDAF does not significantly outperform traditional methods like BM25 in terms of answer accuracy, it excels in citation traceability and provides complete provenance chains for retrieved facts. AI
IMPACT Enhances trust and auditability for LLMs in regulated financial sectors, potentially accelerating enterprise adoption.
RANK_REASON The cluster contains an academic paper detailing a new framework for LLM analytics.
Read on arXiv cs.IR (Information Retrieval) →
- BM25
- Context-Aware Relevance Propagation
- FinanceBench
- KDAF
- Knowledge-Driven Analytics Framework
- LLM
- Auditable by Construction: An Ontology-Driven Framework for Trustworthy LLM Analytics in Enterprise Finance
- Financial Planning and Analysis
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