SPEAR: The New Face of Automatic Prompt Engineering
SPEAR, a novel agentic optimizer, reshapes prompt engineering by leveraging a Python sandbox and strategic error analysis, outperforming its predecessors across multiple industrial tasks.
SPEAR, a novel agentic optimizer, reshapes prompt engineering by leveraging a Python sandbox and strategic error analysis, outperforming its predecessors across multiple industrial tasks.
Conv-to-Bench transforms user-assistant dialogues into verifiable checklists, challenging traditional evaluation benchmarks. This could redefine how we assess AI scalability.
SEAL, a new framework, addresses the challenges of knowledge-based conversational AI with agentic learning, promising enhanced efficiency and accuracy.