most citedTable Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks

14 citations · 17 across the 8 of their papers we have counts for

collaborators

8 papers

cs.SE2023

SoTaNa: The Open-Source Software Development Assistant

Ensheng Shi, Fengji Zhang, Yanlin Wang +6

Software development plays a crucial role in driving innovation and efficiency across modern societies. To meet the demands of this dynamic field, there is a growing need for an ef…

cs.CV2023

GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training

Xinchi Deng, Han Shi, Runhui Huang +7

Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, on…

cs.IR20231 cited

On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

Jiayan Guo, Lun Du, Xu Chen +5

Collaborative filtering (CF) is an important research direction in recommender systems that aims to make recommendations given the information on user-item interactions. Graph CF h…

cs.DB2023

Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines

Dezhan Tu, Yeye He, Weiwei Cui +5

Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications. Crucially, these pipelines are \em…

cs.SE20231 cited

Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond

Ensheng Shi, Yanlin Wang, Hongyu Zhang +4

Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has achieved great success in many software testing and analysis tasks. While effective and preva…

cs.LG2022

Learning Rate Perturbation: A Generic Plugin of Learning Rate Schedule towards Flatter Local Minima

Hengyu Liu, Qiang Fu, Lun Du +4

Learning rate is one of the most important hyper-parameters that has a significant influence on neural network training. Learning rate schedules are widely used in real practice to…