TwinHash: Two-Sided Object Identity Management for Time- and Energy-Efficient Agentic Workflows

arXiv:2611.09254v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) services interleave large language model (LLM) generation with external tool execution, and increasingly rely on search-based workflows that repeatedly revisit shared reasoning states and computations. These patterns create substantial redundancy across tool outputs, LLM responses, and key-value (KV) prefixes, yet existing serving systems primarily optimize shared prompt prefixes, while naive input-keyed caching is unsafe when identical requests produce different outputs.