arXiv Artificial Intelligence

SimpleWikiSearch: A Clean Offline Wikipedia Environment for Agentic Search

SimpleWikiSearch: A Clean Offline Wikipedia Environment for Agentic Search

Quick summary

arXiv:2607.26070v1 Announce Type: cross Abstract: Large language model (LLM)-based agentic search systems are often evaluated as if the underlying LLM were the only component that matters, yet their measured performance also depends on the surrounding search environment: the Wikipedia snapshot, preprocessing pipeline, chunking policy, retrieval backend, tool schema, observation format, and answer submission rule. These details are frequently under-specified, making it difficult to compare results or reproduce reported baselines. We present SimpleWikiSearch, whose corpus construction, retrieval

Key takeaways

  • arXiv:2607.26070v1 Announce Type: cross Abstract: Large language model (LLM)-based agentic search systems are often evaluated as if the underlying LLM were the only component that matters, yet their measured performance also depends on the surrounding search environment: the Wikipedia snapshot, preprocessing pipeline, chunking policy, retrieval backend, tool schema, observation format, and answer submission rule.
  • These details are frequently under-specified, making it difficult to compare results or reproduce reported baselines.
  • We present SimpleWikiSearch, whose corpus construction, retrieval

Why it matters

The significance is not only the legal text but how it changes product design. Decisions around “SimpleWikiSearch: A Clean Offline Wikipedia Environment for Agentic Search” may reshape data collection, model training, output accountability and market access.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗