10 citations · 35 across the 23 of their papers we have counts for
8 papers · 1 filter
CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
Mingjie Liu, Yun-Da Tsai, Wenfei Zhou +1
Despite the significant progress made in code generation with large language models, challenges persist, especially with hardware description languages such as Verilog. This paper…
Benchmarking Large Language Model Uncertainty for Prompt Optimization
Pei-Fu Guo, Yun-Da Tsai, Shou-De Lin
Prompt optimization algorithms for Large Language Models (LLMs) excel in multi-step reasoning but still lack effective uncertainty estimation. This paper introduces a benchmark dat…
Enhance Modality Robustness in Text-Centric Multimodal Alignment with Adversarial Prompting
Yun-Da Tsai, Ting-Yu Yen, Keng-Te Liao +1
Converting different modalities into generalized text, which then serves as input prompts for large language models (LLMs), is a common approach for aligning multimodal models, par…
Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
Yun-Da Tsai, Mingjie Liu, Haoxing Ren
Recent work targeting large language models (LLMs) for code generation demonstrated that increasing the amount of training data through synthetic code generation often leads to exc…
Enhance the Robustness of Text-Centric Multimodal Alignments
Ting-Yu Yen, Yun-Da Tsai, Keng-Te Liao +1
Converting different modalities into general text, serving as input prompts for large language models (LLMs), is a common method to align multimodal models when there is limited pa…
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem
Yun-Ang Wu, Yun-Da Tsai, Shou-De Lin
In this study, we delve into the Thresholding Linear Bandit (TLB) problem, a nuanced domain within stochastic Multi-Armed Bandit (MAB) problems, focusing on maximizing decision acc…
Text-centric Alignment for Multi-Modality Learning
Yun-Da Tsai, Ting-Yu Yen, Pei-Fu Guo +2
This research paper addresses the challenge of modality mismatch in multimodal learning, where the modalities available during inference differ from those available at training. We…
lil'HDoC: An Algorithm for Good Arm Identification under Small Threshold Gap
Tzu-Hsien Tsai, Yun-Da Tsai, Shou-De Lin
Good arm identification (GAI) is a pure-exploration bandit problem in which a single learner outputs an arm as soon as it is identified as a good arm. A good arm is defined as an a…