15 citations · 30 across the 10 of their papers we have counts for
10 papers
Accelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques
Daehoon Gwak, Minhyung Lee, Junwoo Park +1
Diffusion large language models (dLLMs) offer a theoretical advantage in parallel generation over standard autoregressive models. However, parallel generation alone does not guaran…
Not the Example, but the Process: How Self-Generated Examples Enhance LLM Reasoning
Daehoon Gwak, Minseo Jung, Junwoo Park +4
Recent studies have shown that Large Language Models (LLMs) can improve their reasoning performance through self-generated few-shot examples, achieving results comparable to manual…
Reward-Weighted Sampling: Enhancing Non-Autoregressive Characteristics in Masked Diffusion LLMs
Daehoon Gwak, Minseo Jung, Junwoo Park +4
Masked diffusion models (MDMs) offer a promising non-autoregressive alternative for large language modeling. Standard decoding methods for MDMs, such as confidence-based sampling,…
Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Models
Junwoo Park, Hyuck Lee, Dohyun Lee +2
Large Language Models (LLMs) have shown remarkable performance across diverse tasks without domain-specific training, fueling interest in their potential for time-series forecastin…
Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling
Daehoon Gwak, Junwoo Park, Minho Park +4
Predicting future international events from textual information, such as news articles, has tremendous potential for applications in global policy, strategic decision-making, and g…
Self-Supervised Contrastive Learning for Long-term Forecasting
Junwoo Park, Daehoon Gwak, Jaegul Choo +1
Long-term forecasting presents unique challenges due to the time and memory complexity of handling long sequences. Existing methods, which rely on sliding windows to process long s…
Deep Imbalanced Time-series Forecasting via Local Discrepancy Density
Junwoo Park, Jungsoo Lee, Youngin Cho +4
Time-series forecasting models often encounter abrupt changes in a given period of time which generally occur due to unexpected or unknown events. Despite their scarce occurrences…
Enemy Spotted: in-game gun sound dataset for gunshot classification and localization
Junwoo Park, Youngwoo Cho, Gyuhyeon Sim +2
Recently, deep learning-based methods have drawn huge attention due to their simple yet high performance without domain knowledge in sound classification and localization tasks. Ho…
Knowledge Graph-based Question Answering with Electronic Health Records
Junwoo Park, Youngwoo Cho, Haneol Lee +2
Question Answering (QA) is a widely-used framework for developing and evaluating an intelligent machine. In this light, QA on Electronic Health Records (EHR), namely EHR QA, can wo…
What and Where to Translate: Local Mask-based Image-to-Image Translation
Wonwoong Cho, Seunghwan Choi, Junwoo Park +3
Recently, image-to-image translation has obtained significant attention. Among many, those approaches based on an exemplar image that contains the target style information has been…