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AGORA: An Archive-Grounded Benchmark for Agentic Workplace Document Reasoning

Honglin Guo, Qi Zhang, Yu Zhang, Weijie Li, Rui Zheng, Zhikai Lei · Jun 23, 2026

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 42% Moderate protocol signal Freshness: Hot Status: Ready
Automatic Metrics General
  • Large language models are increasingly deployed as agents that reason over documents rather than answer from parametric knowledge.
  • We introduce Agora, a benchmark pairing 362 questions with eight domain collections of 9,664 authentic documents and 372M tokens, far exceeding any model's context window, so agents must explore deliberately rather than scan exhaustively.
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