# LongHarness preprint reports gains in reasoning across large document collections

_Published Monday, October 12, 2026 at 2:53 PM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers report in an arXiv preprint that LongHarness improved AI agents' accuracy when answering questions across large document collections. Using GLM-5.3-Flash, it raised exact-match scores on OfficeQA Pro from 15.8% to 60.2% on V1 and from 4.4% to 61.1% on V2 compared with direct reasoning using the same model.

The system tracks evidence separately from evolving conclusions. Unresolved conclusions guide searches for missing information, while new evidence revises those conclusions; an additional process keeps evidence current and traceable. Its reported OfficeQA Pro results exceeded Claude Code by 12.0 percentage points on V1 and Codex by 18.9 points on V2. The evaluations used GLM-5.3-Flash and Qwen3.8-Flash across four named benchmarks.

## Sources

- [cs.AI updates on arXiv.org](https://arxiv.org/abs/2610.13075)

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Canonical: https://techandbusiness.org/newswire/tcNGux_cyp5mN2fLdqg2G3
Published: 2026-10-12T18:53:15.912Z
Story chronology: 2026-10-12T04:00:00.000Z
Retrieved: 2026-10-12T21:48:57.674Z
Publisher: Tech & Business (techandbusiness.org)