7.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NAVER Cloud (South Korea)KR46 papers
- Seoul National UniversityKR27 papers
- Korea Advanced Institute of Science and TechnologyKR24 papers
- Yonsei UniversityKR17 papers
- Sungkyunkwan UniversityKR12 papers
- Korea UniversityKR9 papers
- Line Corporation (Japan)JP5 papers
- Virginia TechUS5 papers
- Inha UniversityKR4 papers
- Kootenay Association for Science & TechnologyCA4 papers
- University of TorontoCA4 papers
- Hong Kong University of Science and TechnologyHK3 papers
17 papers · 1 filter
Multilingual DistilWhisper: Efficient Distillation of Multi-task Speech Models via Language-Specific Experts
Thomas Palmeira Ferraz, Marcely Zanon Boito, Caroline Brun +1
Whisper is a multitask and multilingual speech model covering 99 languages. It yields commendable automatic speech recognition (ASR) results in a subset of its covered languages, b…
MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
Taewan Kim, Seolyeong Bae, Hyun Ah Kim +4
In the mental health domain, Large Language Models (LLMs) offer promising new opportunities, though their inherent complexity and low controllability have raised questions about th…
HPCClusterScape: Increasing Transparency and Efficiency of Shared High-Performance Computing Clusters for Large-scale AI Models
Heungseok Park, Aeree Cho, Hyojun Jeon +5
The emergence of large-scale AI models, like GPT-4, has significantly impacted academia and industry, driving the demand for high-performance computing (HPC) to accelerate workload…
MvFS: Multi-view Feature Selection for Recommender System
Youngjune Lee, Yeongjong Jeong, Keunchan Park +1
Feature selection, which is a technique to select key features in recommender systems, has received increasing research attention. Recently, Adaptive Feature Selection (AdaFS) has…
EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria
Tae Soo Kim, Yoonjoo Lee, Jamin Shin +2
By simply composing prompts, developers can prototype novel generative applications with Large Language Models (LLMs). To refine prototypes into products, however, developers must…
ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
Woosuk Seo, Chanmo Yang, Young-Ho Kim
Children typically learn to identify and express emotions through sharing their stories and feelings with others, particularly their family. However, it is challenging for parents…
Pruning Self-Attention for Zero-Shot Multi-Speaker Text-to-Speech
Hyungchan Yoon, Changhwan Kim, Eunwoo Song +2
For personalized speech generation, a neural text-to-speech (TTS) model must be successfully implemented with limited data from a target speaker. To this end, the baseline TTS mode…
Controlling the Solo12 Quadruped Robot with Deep Reinforcement Learning
Michel Aractingi, Pierre-Alexandre Léziart, Thomas Flayols +3
Quadruped robots require robust and general locomotion skills to exploit their mobility potential in complex and challenging environments. In this work, we present the first implem…
Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraints
Yujin Baek, Koanho Lee, Dayeon Ki +3
Lexically-constrained NMT (LNMT) aims to incorporate user-provided terminology into translations. Despite its practical advantages, existing work has not evaluated LNMT models unde…
Improved Training for End-to-End Streaming Automatic Speech Recognition Model with Punctuation
Hanbyul Kim, Seunghyun Seo, Lukas Lee +1
Punctuated text prediction is crucial for automatic speech recognition as it enhances readability and impacts downstream natural language processing tasks. In streaming scenarios,…
Task Relation-aware Continual User Representation Learning
Sein Kim, Namkyeong Lee, Donghyun Kim +2
User modeling, which learns to represent users into a low-dimensional representation space based on their past behaviors, got a surge of interest from the industry for providing pe…
An empirical study on speech restoration guided by self supervised speech representation
Jaeuk Byun, Youna Ji, Soo Whan Chung +2
Enhancing speech quality is an indispensable yet difficult task as it is often complicated by a range of degradation factors. In addition to additive noise, reverberation, clipping…
ConQueR: Contextualized Query Reduction using Search Logs
Hye-young Kim, Minjin Choi, Sunkyung Lee +3
Query reformulation is a key mechanism to alleviate the linguistic chasm of query in ad-hoc retrieval. Among various solutions, query reduction effectively removes extraneous terms…
DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models
Sungnyun Kim, Junsoo Lee, Kibeom Hong +2
In this study, we aim to enhance the capabilities of diffusion-based text-to-image (T2I) generation models by integrating diverse modalities beyond textual descriptions within a un…
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment
Minkyu Jeon, Hyeonjin Park, Hyunwoo J. Kim +2
The application of modern machine learning to retinal image analyses offers valuable insights into a broad range of human health conditions beyond ophthalmic diseases. Additionally…
AVscript: Accessible Video Editing with Audio-Visual Scripts
Mina Huh, Saelyne Yang, Yi-Hao Peng +3
Sighted and blind and low vision (BLV) creators alike use videos to communicate with broad audiences. Yet, video editing remains inaccessible to BLV creators. Our formative study r…
Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data
Jing Wei, Sungdong Kim, Hyunhoon Jung +1
Large language models (LLMs) provide a new way to build chatbots by accepting natural language prompts. Yet, it is unclear how to design prompts to power chatbots to carry on natur…