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Videogen-eval: Agent-based system for video generation evaluation

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

citation-role summary

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citation-polarity summary

fields

cs.CV 4

years

2026 3 2025 1

verdicts

UNVERDICTED 4

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background 4

representative citing papers

How Far Are Video Models from True Multimodal Reasoning?

cs.CV · 2026-04-21 · unverdicted · novelty 6.0

Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.

LPM 1.0: Video-based Character Performance Model

cs.CV · 2026-04-09 · unverdicted · novelty 6.0

LPM 1.0 generates infinite-length, identity-stable, real-time audio-visual conversational performances for single characters using a distilled causal diffusion transformer and a new benchmark.

Evolution of Video Generative Foundations

cs.CV · 2026-04-07 · unverdicted · novelty 2.0

This survey traces video generation technology from GANs to diffusion models and then to autoregressive and multimodal approaches while analyzing principles, strengths, and future trends.

citing papers explorer

Showing 4 of 4 citing papers.

  • ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body cs.CV · 2025-12-16 · unverdicted · none · ref 123

    ViBES introduces a speech-language-behavior model using modality-specific transformer experts that jointly generates dialogue and 3D body actions, showing gains over separate co-speech and text-to-motion baselines on multi-turn metrics.

  • How Far Are Video Models from True Multimodal Reasoning? cs.CV · 2026-04-21 · unverdicted · none · ref 83

    Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.

  • LPM 1.0: Video-based Character Performance Model cs.CV · 2026-04-09 · unverdicted · none · ref 84

    LPM 1.0 generates infinite-length, identity-stable, real-time audio-visual conversational performances for single characters using a distilled causal diffusion transformer and a new benchmark.

  • Evolution of Video Generative Foundations cs.CV · 2026-04-07 · unverdicted · none · ref 168

    This survey traces video generation technology from GANs to diffusion models and then to autoregressive and multimodal approaches while analyzing principles, strengths, and future trends.