1 citations · 1 across the 9 of their papers we have counts for
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Unraveling Arithmetic in Large Language Models: The Role of Algebraic Structures
Fu-Chieh Chang, You-Chen Lin, Pei-Yuan Wu
Large language models (LLMs) have demonstrated remarkable mathematical capabilities, largely driven by chain-of-thought (CoT) prompting, which decomposes complex reasoning into ste…
RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner
Fu-Chieh Chang, Yu-Ting Lee, Hui-Ying Shih +2
The reasoning abilities of large language models (LLMs) have improved with chain-of-thought (CoT) prompting, allowing models to solve complex tasks stepwise. However, training CoT…
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning
Yen-Ru Lai, Fu-Chieh Chang, Pei-Yuan Wu
Offline reinforcement learning (RL) learns policies from a fixed dataset, but often requires large amounts of data. The challenge arises when labeled datasets are expensive, especi…
CAPM: Fast and Robust Verification on Maxpool-based CNN via Dual Network
Jia-Hau Bai, Chi-Ting Liu, Yu Wang +2
This study uses CAPM (Convex Adversarial Polytope for Maxpool-based CNN) to improve the verified bound for general purpose maxpool-based convolutional neural networks (CNNs) under…