1 citations · 1 across the 4 of their papers we have counts for
4 papers
Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detection
Seongmin Park, Minjae Lee, Junwon Choi +1
Pillar-based 3D object detection has gained traction in self-driving technology due to its speed and accuracy facilitated by the artificial densification of pillars for GPU-friendl…
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment
Janghwan Lee, Seongmin Park, Sukjin Hong +3
The rapid advancement of large language models (LLMs) has facilitated their transformation into conversational chatbots that can grasp contextual nuances and generate pertinent sen…
Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers
Minsoo Kim, Kyuhong Shim, Seongmin Park +2
Pre-trained Transformer models such as BERT have shown great success in a wide range of applications, but at the cost of substantial increases in model complexity. Quantization-awa…
Exploring Attention Map Reuse for Efficient Transformer Neural Networks
Kyuhong Shim, Jungwook Choi, Wonyong Sung
Transformer-based deep neural networks have achieved great success in various sequence applications due to their powerful ability to model long-range dependency. The key module of…