Web2BigTable system enhances LLM web search with bi-level agent architecture

Researchers have developed Web2BigTable, a novel bi-level multi-agent system designed for large-scale internet information search and extraction. This framework features an orchestrator that breaks down tasks for parallel processing by lower-level worker agents. Through a continuous run-verify-reflect cycle and a shared workspace, Web2BigTable enhances decomposition and execution, leading to improved data consistency and coverage. AI

IMPACT Sets new SOTA on web search benchmarks, potentially improving data aggregation and reasoning capabilities for AI systems.

RANK_REASON This is a research paper detailing a new system and its benchmark performance.

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• arXiv
• Web2BigTable
• WideSearch
• XBench-DeepSearch

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