most citedArtificial Intelligence for Operations Research: Revolutionizing the Operations Research Process

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

DeTriever: Decoder-representation-based Retriever for Improving NL2SQL In-Context Learning

Yuxi Feng, Raymond Li, Zhenan Fan +4

While in-context Learning (ICL) has proven to be an effective technique to improve the performance of Large Language Models (LLMs) in a variety of complex tasks, notably in transla…

cs.CL2024

SQL-Encoder: Improving NL2SQL In-Context Learning Through a Context-Aware Encoder

Mohammadreza Pourreza, Davood Rafiei, Yuxi Feng +3

Detecting structural similarity between queries is essential for selecting examples in in-context learning models. However, assessing structural similarity based solely on the natu…

cs.AI2024

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications

Xijun Li, Fangzhou Zhu, Hui-Ling Zhen +23

In an era of digital ubiquity, efficient resource management and decision-making are paramount across numerous industries. To this end, we present a comprehensive study on the inte…

math.OC20244 cited

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process

Zhenan Fan, Bissan Ghaddar, Xinglu Wang +3

The rapid advancement of artificial intelligence (AI) techniques has opened up new opportunities to revolutionize various fields, including operations research (OR). This survey pa…

cs.LG20221 cited

Knowledge-Injected Federated Learning

Zhenan Fan, Zirui Zhou, Jian Pei +4

Federated learning is an emerging technique for training models from decentralized data sets. In many applications, data owners participating in the federated learning system hold…