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Language- guided image tokenization for generation

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

2 Pith papers citing it

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cs.CV 1 cs.RO 1

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2026 1 2025 1

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representative citing papers

DiffusionBench: On Holistic Evaluation of Diffusion Transformers

cs.CV · 2026-06-23 · conditional · novelty 6.0

NanoGen unifies DiT training on ImageNet and T2I, reveals negative Pearson correlations (-0.377 to -0.580) in method rankings across metrics from 21 models, and motivates DiffusionBench for holistic evaluation.

UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

cs.RO · 2025-05-09 · unverdicted · novelty 6.0

UniVLA trains cross-embodiment vision-language-action policies from unlabeled videos via a latent action model in DINO space, beating OpenVLA on benchmarks with 1/20th pretraining compute and 1/10th downstream data.

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Showing 2 of 2 citing papers.

  • DiffusionBench: On Holistic Evaluation of Diffusion Transformers cs.CV · 2026-06-23 · conditional · none · ref 36

    NanoGen unifies DiT training on ImageNet and T2I, reveals negative Pearson correlations (-0.377 to -0.580) in method rankings across metrics from 21 models, and motivates DiffusionBench for holistic evaluation.

  • UniVLA: Learning to Act Anywhere with Task-centric Latent Actions cs.RO · 2025-05-09 · unverdicted · none · ref 89

    UniVLA trains cross-embodiment vision-language-action policies from unlabeled videos via a latent action model in DINO space, beating OpenVLA on benchmarks with 1/20th pretraining compute and 1/10th downstream data.