112 citations · 578 across the 17 of their papers we have counts for
17 papers
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…
Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach
Saar Kuzi, Mingyang Zhang, Cheng Li +2
Search engines often follow a two-phase paradigm where in the first stage (the retrieval stage) an initial set of documents is retrieved and in the second stage (the re-ranking sta…