5 citations · 20 across the 30 of their papers we have counts for
6 papers · 1 filter
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation
Yi-Chang Chen, Po-Chun Hsu, Chan-Jan Hsu +1
Large language models (LLMs) have significantly advanced autonomous agents, particularly in zero-shot tool usage, also known as function calling. This research delves into enhancin…
FineWeb-zhtw: Scalable Curation of Traditional Chinese Text Data from the Web
Cheng-Wei Lin, Wan-Hsuan Hsieh, Kai-Xin Guan +6
The quality and size of a pretraining dataset significantly influence the performance of large language models (LLMs). While there have been numerous efforts in the curation of suc…
Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
Davide Buffelli, Jamie McGowan, Wangkun Xu +4
Second-order optimization has been shown to accelerate the training of deep neural networks in many applications, often yielding faster progress per iteration on the training loss…
RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues
Tzu-Lin Kuo, Feng-Ting Liao, Mu-Wei Hsieh +3
In real-world applications with Large Language Models (LLMs), external retrieval mechanisms - such as Search-Augmented Generation (SAG), tool utilization, and Retrieval-Augmented G…
Let's Fuse Step by Step: A Generative Fusion Decoding Algorithm with LLMs for Robust and Instruction-Aware ASR and OCR
Chan-Jan Hsu, Yi-Chang Chen, Feng-Ting Liao +4
We propose "Generative Fusion Decoding" (GFD), a novel shallow fusion framework designed to integrate large language models (LLMs) into cross-modal text recognition systems for aut…
Breeze-7B Technical Report
Chan-Jan Hsu, Chang-Le Liu, Feng-Ting Liao +3
Breeze-7B is an open-source language model based on Mistral-7B, designed to address the need for improved language comprehension and chatbot-oriented capabilities in Traditional Ch…