4 citations · 4 across the 5 of their papers we have counts for
5 papers
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…
GLOVA: Global and Local Variation-Aware Analog Circuit Design with Risk-Sensitive Reinforcement Learning
Dongjun Kim, Junwoo Park, Chaehyeon Shin +8
Analog/mixed-signal circuit design encounters significant challenges due to performance degradation from process, voltage, and temperature (PVT) variations. To achieve commercial-g…
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…