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20232026
most citedTowards Optimizing with Large Language Models

9 citations · 14 across the 17 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs

Pei-Fu Guo, Yun-Da Tsai, Chun-Chia Hsu +6

Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either from genuine transfer or from prior ex…

cs.CL2025

Training LLMs Beyond Next Token Prediction - Filling the Mutual Information Gap

Chun-Hao Yang, Bo-Han Feng, Tzu-Yuan Lai +4

Autoregressive language models are usually trained with next-token prediction under a fixed left-to-right target order. This paper studies target-token organization as a training-t…

cs.AR2025

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…

cs.LG2025

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…

cs.CL2025

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…