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What does EntityBench report about keeping characters, objects and locations consistent across up to 50 shots, under which metrics and settings, and which systems were compared?

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-23 · art_01M5MBYAQ7JME9SB833W8696GN

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EntityBench (arXiv 2605.15199v1, 14 May 2026, ByteDance/Rice) is a benchmark of 140 episodes and 2,491 shots with per-shot schedules for characters, objects and locations, scored on 51 metrics in three pillars. Four systems were compared: HoloCine, CineTrans, StoryMem and the authors' EntityMem. The authors report that cross-shot consistency drops with the number of shots between appearances, that DINOv2 face similarity and LLM identity accuracy rank the systems differently, and that EntityMem (their own per-entity reference memory on top of StoryMem, no extra training) has the highest LLM character-identity scores (llm_face_accuracy 0.406 vs 0.226 StoryMem, 0.228 HoloCine, 0.091 CineTrans). Everything is authors-run; no code or data link was found in the paper bytes.

EntityBench (arXiv 2605.15199v1, 14 May 2026, ByteDance/Rice) is a benchmark of 140 episodes and 2,491 shots with per-shot schedules for characters, objects and locations, scored on 51 metrics in three pillars. Four systems were compared: HoloCine, CineTrans, StoryMem and the authors' EntityMem. The authors report that cross-shot consistency drops with the number of shots between appearances, that DINOv2 face similarity and LLM identity accuracy rank the systems differently, and that EntityMem (their own per-entity reference memory on top of StoryMem, no extra training) has the highest LLM character-identity scores (llm_face_accuracy 0.406 vs 0.226 StoryMem, 0.228 HoloCine, 0.091 CineTrans). Everything is authors-run; no code or data link was found in the paper bytes. Curator qualifications: All excerpts located; DINOv2 vs LLM ranking disagreement (StoryMem vs EntityMem) kept. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.
Structured fields
{
  "citations": [
    {
      "url": "https://arxiv.org/html/2605.15199v1",
      "note": "candidate evidence excerpts"
    }
  ]
}

Evidence claims

  • [sourced_fact] EntityBench (arXiv 2605.15199v1, 14 May 2026, ByteDance/Rice) is a benchmark of 140 episodes and 2,491 shots with per-shot schedules for characters, objects and locations, scored on 51 metrics in three pillars. Four systems were compared: HoloCine, CineTrans, StoryMem and the authors' EntityMem. The authors report that cross-shot consistency drops with the number of shots between appearances, that DINOv2 face similarity and LLM identity accuracy rank the systems differently, and that EntityMem (their own per-entity reference memory on top of StoryMem, no extra training) has the highest LLM character-identity scores (llm_face_accuracy 0.406 vs 0.226 StoryMem, 0.228 HoloCine, 0.091 CineTrans). Everything is authors-run; no code or data link was found in the paper bytes. · locator: candidate evidence excerpts source

Rights

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