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New benchmark LongShOTBench tests omni-modal reasoning in long videos

Researchers have introduced LongShOTBench, a new benchmark designed to evaluate omni-modal reasoning capabilities in long videos. This benchmark integrates vision, speech, and ambient audio, offering detailed rubrics for diagnostic evaluation. Alongside the benchmark, they developed LongShOTAgent, a training-free agent that demonstrates strong performance on the new testbed, outperforming current multi-modal large language models. AI

RANK_REASON The cluster describes the release of a new academic benchmark and associated agent for evaluating AI capabilities in long-form video understanding. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Jinxing Zhou, Sahal Shaji Mullappilly, Mohammad Almansoori, Noor Ahsan, Beknur Kalmakhanbet, Sambal Shikhar, Rishabh Lalla, Jean Lahoud, Mariette Awad, Fahad Shahbaz Khan, Salman Khan, Rao Muhammad An… ·

    A Benchmark for Omni-Modal Reasoning in Long Videos

    arXiv:2512.16978v2 Announce Type: replace Abstract: Long-form omni-modal video understanding requires integrating vision, speech, and ambient audio with coherent long-context reasoning. Existing video benchmarks often trade off temporal scale, modality coverage, open-ended intera…