5 citations · 5 across the 4 of their papers we have counts for
5 papers
OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation
Seungjae Moon, Seunghyun Oh, Youngmin Ro
Training-free open-vocabulary semantic segmentation(TF-OVSS) has recently attracted attention for its ability to perform dense prediction by leveraging the pretrained knowledge of…
RecycleLoRA: Rank-Revealing QR-Based Dual-LoRA Subspace Adaptation for Domain Generalized Semantic Segmentation
Chanseul Cho, Seokju Yun, Jeaseong Jeon +2
Domain Generalized Semantic Segmentation (DGSS) aims to maintain robust performance across unseen target domains. Vision Foundation Models (VFMs) offer rich multi-domain knowledge…
LPU: A Latency-Optimized and Highly Scalable Processor for Large Language Model Inference
Seungjae Moon, Jung-Hoon Kim, Junsoo Kim +14
The explosive arrival of OpenAI's ChatGPT has fueled the globalization of large language model (LLM), which consists of billions of pretrained parameters that embodies the aspects…
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation
Seongmin Hong, Seungjae Moon, Junsoo Kim +4
Transformer is a deep learning language model widely used for natural language processing (NLP) services in datacenters. Among transformer models, Generative Pre-trained Transforme…
Exploration of Systolic-Vector Architecture with Resource Scheduling for Dynamic ML Workloads
Jung-Hoon Kim, Sungyeob Yoo, Seungjae Moon +1
As artificial intelligence (AI) and machine learning (ML) technologies disrupt a wide range of industries, cloud datacenters face ever-increasing demand in inference workloads. How…