Auto86%Harbor: pendingMultimodalInstruction Following

ReTurn

ReTurn: Selective History Use across Multimodal Turns

ReTurn is a 7,000-task omni-modal benchmark evaluating selective history use in multi-turn conversations via visual and audio evidence.

How to run

ltb · return
$ npm i -g lettokenburn-cli
$ ltb bench info return

External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

12 sourced entries
HarnessSourceConfidenceLink
StepAudio 398.4N/AIndependentmediumOct 8, 2026arxiv.org
Audio Flamingo 397.8N/AIndependentmediumOct 8, 2026arxiv.org
Doubao-Seed-2.0-Lite97.4N/AIndependentmediumOct 8, 2026arxiv.org
Qwen 3.8 Omni Flash96.2N/AIndependentmediumOct 8, 2026arxiv.org
Qwen3-Omni95.0N/AIndependentmediumOct 8, 2026arxiv.org
Qwen3.7 Plus94.9N/AIndependentmediumOct 8, 2026arxiv.org
MiniCPM-o 4.593.9N/AIndependentmediumOct 8, 2026arxiv.org
MiMo V2.592.6N/AIndependentmediumOct 8, 2026arxiv.org
Qwen3-VL92.0N/AIndependentmediumOct 8, 2026arxiv.org
Nemotron-3-Nano-Omni90.1N/AIndependentmediumOct 8, 2026arxiv.org
MiniCPM-V-4-587.5N/AIndependentmediumOct 8, 2026arxiv.org
InternVL3.580.8N/AIndependentmediumOct 8, 2026arxiv.org

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

Reproduced by the community

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About

ReTurn comprises 7,000 base tasks spanning visual and audio evidence, organized into task-carrying (Reconfirm/Reground) and evidence-carrying (Retrieve/Rebind) history conditions with matched single-turn references.

It evaluates models using open-ended and multiple-choice formats, measuring accuracy drops from direct input to conversational settings to assess history selection and interference handling.