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Kuniaki Saito

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#artificial intelligence Preprint Sep 2026

The Devil is in the Spectrum Bias: Spectrum-Balanced Feature Matching for Robust Representation Distillation

Spectrum-Balanced Feature Matching, SpecMatch, a simple objective that adaptively emphasizes under-optimized spectral directions while preserving the relative importance of dominant directions is proposed, which improves downstream adaptation across diverse tasks, including image classification, anomaly detection, medi...

Kuniaki Saito, Y. Ushiku · 0 citations
#artificial intelligence Preprint Sep 2026

VidOmni-Bench: A Benchmark for Fine-Grained Video Understanding via Spatio-Temporal Event Verification across Complexity and Duration

VidOmni-Bench is introduced, a benchmark that requires models to verify whether each event in dense video captions is supported by the video, and reveals three key findings: Video-LLMs frequently generate hallucinated descriptions in dense video captioning, and they also struggle as verifiers.

Changbeen Kim, Jun-Qing Chang, Kipyo Kim et al. · 0 citations
Preprint Jul 2026

CLAP: Direct VLM-to-VLA Adaptation via Language-Action Grounding

CLAP (Causal Language-Action Prediction), which prepends each numeric action sequence with a natural-language action description, causally conditioning precise action-token prediction on a language-action plan without modifying the backbone architecture, enabling controlled analysis of VLM-to-VLA capability transfer.

Yuri Ishitoya, Jeremy Siburian, Masashi Hamaya et al. · 0 citations

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