In agentic AI systems, frozen foundation models are increasingly deployed as closed-weight API endpoints, making downstream adaptation possible only through the inputs and inference procedures surrounding the model. As a result, for each input query, two coupled decisions largely determine both answer quality and token...
Xi Xiao, Yun-Bei Zhang, Chen Liu et al.· 0 citations
The proposed NumCache, which compresses SEC filings into KV caches initialized from numerically dense regions and trained directly on financial QAs, is evaluated, which highlights cache-based retrieval with number-preserving representations as an effective approach for long-context financial QA.
Eftychia Makri, Peiwen Li, Yi-Dong Jiang et al.· Proceedings of the 32nd ACM...· 0 citations
Large Language Models (LLMs) are increasingly deployed in financial applications, particularly for interpreting U.S. Securities and Exchange Commission (SEC) filings. However, financial QA over these filings is challenging, as they are extremely long, numerically dense, and often require cross-document reasoning. Exist...
Eftychia Makri, Peiwen Li, Yidong Jiang et al.· Proceedings of the 32nd ACM...· 0 citations
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