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

> Large language models are increasingly deployed as agents that reason over documents rather than answer from parametric knowledge. We study archive-grounded reasoning: locating sparse evidence across a large, messy collection of workplace files, reconciling inconsistent terminology, units, and time conventions, and computing an answer. Existing benchmarks address only parts of this setting and none jointly stresses a...

**来源信息**
- **来源**：HuggingFace Daily Papers（社区热门论文）
- **分类**：论文
- **发布时间**：2026-06-24 08:00（北京时间）
- **原文**：[打开原文](https://huggingface.co/papers/2606.24526)