MIOH C

AI benchmark

Tier
C why
Snapshot

What is MIOH?

MIOH measures object hallucination in multimodal LLMs across multi-image scenarios, covering existence, counting, attribute and position tasks under different reasoning patterns and adversarial pressures.

  • Media mostly

    “we introduce MIOH, a fine-grained multi-image object hallucination benchmark that systematically evaluates object hallucination across four foundational tasks”
    arxiv.org/abs/2608.30653v1 ↗

  • General capability

    “MIOH provides a controlled framework for analyzing multi-image object hallucination”
    arxiv.org/abs/2608.30653v1 ↗

Paper: arxiv.org/abs/2608.30653v1 ↗

Tier C

C

Niche: a handful of models scored, or built by an RL vendor.

How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.

  • 9 models scored
  • in curated RL directories (1 pt)
How we got to tier C
  1. Adoption: 9 models scored. Tier C.
  2. Not yet read on X.
  3. In curated RL directories: 1 point, a floor of none.
  4. Confirmed: a line from its own site or paper places it.

A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.

Where MIOH sits

Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map

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Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-10-19 snapshot.