5 papers
An Efficient Algorithm for Thresholding Monte Carlo Tree Search
Shoma Nameki, Atsuyoshi Nakamura, Junpei Komiyama +1
We introduce the Thresholding Monte Carlo Tree Search problem, in which, given a tree and a threshold , a player must answer whether the root node value of $\mathc…
Training LLMs Beyond Next Token Prediction -- Filling the Mutual Information Gap
Chun-Hao Yang, Bo-Han Feng, Tzu-Yuan Lai +3
Optimizing training performance in large language models (LLMs) remains an essential challenge, particularly in improving model performance while maintaining computational costs. T…
Multimodal Chip Physical Design Engineer Assistant
Yun-Da Tsai, Chang-Yu Chao, Liang-Yeh Shen +7
Modern chip physical design relies heavily on Electronic Design Automation (EDA) tools, which often struggle to provide interpretable feedback or actionable guidance for improving…
Uncertainty Profiles for LLMs: Uncertainty Source Decomposition and Adaptive Model-Metric Selection
Pei-Fu Guo, Yun-Da Tsai, Shou-De Lin
Large language models (LLMs) often generate fluent but factually incorrect outputs, known as hallucinations, which undermine their reliability in real-world applications. While unc…
PLHF: Prompt Optimization with Few-Shot Human Feedback
Chun-Pai Yang, Kan Zheng, Shou-De Lin
Automatic prompt optimization frameworks are developed to obtain suitable prompts for large language models (LLMs) with respect to desired output quality metrics. Although existing…