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Joo-Young Kim

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#generative ai Oct 2026

A 11.0-TOPS/W Diffusion Accelerator With Temporal Data Reuse for Real-Time Text-to-Motion Generation

Text-to-motion models are AI systems that generate human motion sequences directly from natural language descriptions, serving as key enablers for immersive virtual avatars and interactive digital humans in AR/VR ecosystems. However, state-of-the-art text-to-motion diffusion models suffer from substantial computational...

Sungwoong Yune, Jieon Yoon, Hangyeol Lee et al. · 1 citation
Preprint Aug 2026

NOVA: Technology-Architecture Co-Design of Near-Memory Processing for Attention-SSM-MoE Hybrid LLM Inference

NoVA is proposed, a technology-architecture co-designed NMP system that overcomes both walls and achieves on average 4.5x higher throughput, 69.8% lower end-to-end latency, and 5x better energy efficiency over a GPU baseline, with only 3.9% area overhead and no loss in memory capacity.

In Jung, Jaeha Min, Joo-Young Kim · 0 citations

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