AIBullisharXiv – CS AI · 6h ago7/10
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Absorbing Complexity: An Interaction-Native Knowledge Harness for Financial LLM Agents
Researchers propose InKH, an architecture for financial AI agents that maintains persistent context about users, portfolios, and market conditions rather than forcing users to repeatedly restate information. In controlled benchmarks, InKH achieves 82% latency reduction and 96% improvement in stale-knowledge elimination compared to existing approaches, suggesting that AI financial tools succeed by absorbing operational complexity into their systems rather than delegating it to users.