most citedDiagnosing Infeasible Optimization Problems Using Large Language Models

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

XCoOp: Explainable Prompt Learning for Computer-Aided Diagnosis via Concept-guided Context Optimization

Yequan Bie, Luyang Luo, Zhixuan Chen +1

Utilizing potent representations of the large vision-language models (VLMs) to accomplish various downstream tasks has attracted increasing attention. Within this research field, s…

eess.SP2024

Distributed Task-Oriented Communication Networks with Multimodal Semantic Relay and Edge Intelligence

Jie Guo, Hao Chen, Bin Song +5

In this article, we present a novel framework, named distributed task-oriented communication networks (DTCN), based on recent advances in multimodal semantic transmission and edge…

cs.CL2024

TAROT: A Hierarchical Framework with Multitask Co-Pretraining on Semi-Structured Data towards Effective Person-Job Fit

Yihan Cao, Xu Chen, Lun Du +7

Person-job fit is an essential part of online recruitment platforms in serving various downstream applications like Job Search and Candidate Recommendation. Recently, pretrained la…

cs.HC20233 cited

Diagnosing Infeasible Optimization Problems Using Large Language Models

Hao Chen, Gonzalo E. Constante-Flores, Can Li

Decision-making problems can be represented as mathematical optimization models, finding wide applications in fields such as economics, engineering and manufacturing, transportatio…

cs.CL2023

AIDA: Legal Judgment Predictions for Non-Professional Fact Descriptions via Partial-and-Imbalanced Domain Adaptation

Guangyi Xiao, Xinlong Liu, Hao Chen +2

In this paper, we study the problem of legal domain adaptation problem from an imbalanced source domain to a partial target domain. The task aims to improve legal judgment predicti…