8 citations · 10 across the 8 of their papers we have counts for
4 papers · 1 filter
Quantize the Target, Quantize the Drafter: Efficient Inference with Qwen3.5-4B
Jaeyeon Kim, Jewon Lee, Bo-Kyeong Kim
This report describes our approach to the Efficient Qwen Competition, where the goal is to enable low-latency serving of Qwen3.5-4B on a resource-constrained NVIDIA A10G GPU. Our s…
LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights
Thibault Castells, Hyoung-Kyu Song, Bo-Kyeong Kim +1
Latent Diffusion Models (LDMs) have emerged as powerful generative models, known for delivering remarkable results under constrained computational resources. However, deploying LDM…
EdgeFusion: On-Device Text-to-Image Generation
Thibault Castells, Hyoung-Kyu Song, Tairen Piao +6
The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application. To tackle this challenge, recent…
Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods
Bo-Kyeong Kim, Geonmin Kim, Tae-Ho Kim +4
Structured pruning of modern large language models (LLMs) has emerged as a way of decreasing their high computational needs. Width pruning reduces the size of projection weight mat…