112 citations · 578 across the 17 of their papers we have counts for
5 papers · 1 filter
Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Zheng Yuan, Hongyi Yuan, Chengpeng Li +5
Mathematical reasoning is a challenging task for large language models (LLMs), while the scaling relationship of it with respect to LLM capacity is under-explored. In this paper, w…
Teach LLMs to Personalize -- An Approach inspired by Writing Education
Cheng Li, Mingyang Zhang, Qiaozhu Mei +4
Personalized text generation is an emerging research area that has attracted much attention in recent years. Most studies in this direction focus on a particular domain by designin…
DDNAS: Discretized Differentiable Neural Architecture Search for Text Classification
Kuan-Chun Chen, Cheng-Te Li, Kuo-Jung Lee
Neural Architecture Search (NAS) has shown promising capability in learning text representation. However, existing text-based NAS neither performs a learnable fusion of neural oper…
TabGSL: Graph Structure Learning for Tabular Data Prediction
Jay Chiehen Liao, Cheng-Te Li
This work presents a novel approach to tabular data prediction leveraging graph structure learning and graph neural networks. Despite the prevalence of tabular data in real-world a…
SUVR: A Search-based Approach to Unsupervised Visual Representation Learning
Yi-Zhan Xu, Chih-Yao Chen, Cheng-Te Li
Unsupervised learning has grown in popularity because of the difficulty of collecting annotated data and the development of modern frameworks that allow us to learn from unlabeled…