Domain-Specific Embeddings: Finance Edition (voyage-finance-2)

voyage-finance-2 is a newly launched finance domain-specific embedding model that excels in financial retrieval tasks, outperforming other models like OpenAI and Cohere by an average of 7% and 12%, respectively, across 11 finance retrieval datasets. This model features a 32K context length, significantly longer than its competitors, and is part of a broader portfolio that includes voyage-law-2 and voyage-code-2. It is designed to address challenging retrieval problems by focusing parameter capacity on specific domains, thereby enhancing performance in expertise-intensive areas. Evaluated on datasets like TAT-QA, FinanceBench, and others, voyage-finance-2 demonstrated superior performance using the normalized discounted cumulative gain (NDCG@10) metric, proving its efficacy in tasks involving financial news, public filings, and financial reports. This model promises to enhance Gen AI applications in the financial sector, offering users a tool optimized for high-quality retrieval and encouraging further domain-specific innovation.