14 citations · 42 across the 15 of their papers we have counts for
15 papers
Open World Classification with Adaptive Negative Samples
Ke Bai, Guoyin Wang, Jiwei Li +5
Open world classification is a task in natural language processing with key practical relevance and impact. Since the open or {\em unknown} category data only manifests in the infe…
Ranking-Enhanced Unsupervised Sentence Representation Learning
Yeon Seonwoo, Guoyin Wang, Changmin Seo +6
Unsupervised sentence representation learning has progressed through contrastive learning and data augmentation methods such as dropout masking. Despite this progress, sentence enc…
Continuous-Time Video Generation via Learning Motion Dynamics with Neural ODE
Kangyeol Kim, Sunghyun Park, Junsoo Lee +4
In order to perform unconditional video generation, we must learn the distribution of the real-world videos. In an effort to synthesize high-quality videos, various studies attempt…
Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)
Taewon Kang, Sunghyun Park, Seunghwan Choi +1
Image-based virtual try-on provides the capacity to transfer a clothing item onto a photo of a given person, which is usually accomplished by warping the item to a given human pose…
Collage: Seamless Integration of Deep Learning Backends with Automatic Placement
Byungsoo Jeon, Sunghyun Park, Peiyuan Liao +3
The strong demand for efficient and performant deployment of Deep Learning (DL) applications prompts the rapid development of a rich DL ecosystem. To keep up with this fast advance…
Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
Jungsoo Lee, Jooyeol Yun, Sunghyun Park +2
Despite the unprecedented improvement of face recognition, existing face recognition models still show considerably low performances in determining whether a pair of child and adul…
Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skills
Sangbeom Park, Yoonbyung Chai, Sunghyun Park +3
In this paper, we present a semi-autonomous teleoperation framework for a pick-and-place task using an RGB-D sensor. In particular, we assume that the target object is located in a…
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
Boseop Kim, HyoungSeok Kim, Sang-Woo Lee +34
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less report…
Learning Slice-Aware Representations with Mixture of Attentions
Cheng Wang, Sungjin Lee, Sunghyun Park +3
Real-world machine learning systems are achieving remarkable performance in terms of coarse-grained metrics like overall accuracy and F-1 score. However, model improvement and deve…
Handling Long-Tail Queries with Slice-Aware Conversational Systems
Cheng Wang, Sun Kim, Taiwoo Park +5
We have been witnessing the usefulness of conversational AI systems such as Siri and Alexa, directly impacting our daily lives. These systems normally rely on machine learning mode…
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration
Han Li, Sunghyun Park, Aswarth Dara +5
Current state-of-the-art large-scale conversational AI or intelligent digital assistant systems in industry comprises a set of components such as Automatic Speech Recognition (ASR)…
VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization
Seunghwan Choi, Sunghyun Park, Minsoo Lee +1
The task of image-based virtual try-on aims to transfer a target clothing item onto the corresponding region of a person, which is commonly tackled by fitting the item to the desir…
K-Hairstyle: A Large-scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification
Taewoo Kim, Chaeyeon Chung, Sunghyun Park +5
The hair and beauty industry is a fast-growing industry. This led to the development of various applications, such as virtual hair dyeing or hairstyle transfer, to satisfy the cust…
A scalable framework for learning from implicit user feedback to improve natural language understanding in large-scale conversational AI systems
Sunghyun Park, Han Li, Ameen Patel +5
Natural Language Understanding (NLU) is an established component within a conversational AI or digital assistant system, and it is responsible for producing semantic understanding…
Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation
Sunghyun Park, Kangyeol Kim, Junsoo Lee +4
Video generation models often operate under the assumption of fixed frame rates, which leads to suboptimal performance when it comes to handling flexible frame rates (e.g., increas…