activity
20182025
most citedRecent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

30 citations · 43 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI2025

AI Pangaea: Unifying Intelligence Islands for Adapting Myriad Tasks

Jianlong Chang, Haixin Wang, Zhiyuan Dang +11

The pursuit of artificial general intelligence continuously demands generalization in one model across myriad tasks, even those not seen before. However, current AI models are isol…

cs.LG2024★ 30 cited

Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Haixin Wang, Yadi Cao, Zijie Huang +13

This paper explores the recent advancements in enhancing Computational Fluid Dynamics (CFD) tasks through Machine Learning (ML) techniques. We begin by introducing fundamental conc…

cs.CL2023

When Parameter-efficient Tuning Meets General-purpose Vision-language Models

Yihang Zhai, Haixin Wang, Jianlong Chang +4

Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate mul…

cs.CV2023★ 6 cited

Parameter-efficient Tuning of Large-scale Multimodal Foundation Model

Haixin Wang, Xinlong Yang, Jianlong Chang +5

Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…

cs.CL2023★ 1 cited

Exploiting Pseudo Image Captions for Multimodal Summarization

Chaoya Jiang, Rui Xie, Wei Ye +2

Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge of (partial) false negatives. In this paper, we study this problem from the perspective of…

cs.CV2023★ 2 cited

LION: Implicit Vision Prompt Tuning

Haixin Wang, Jianlong Chang, Xiao Luo +3

Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has pr…

cs.CL2021

Frequency-Aware Contrastive Learning for Neural Machine Translation

Tong Zhang, Wei Ye, Baosong Yang +7

Low-frequency word prediction remains a challenge in modern neural machine translation (NMT) systems. Recent adaptive training methods promote the output of infrequent words by emp…

cs.CL2021★ 2 cited

Exploiting Method Names to Improve Code Summarization: A Deliberation Multi-Task Learning Approach

Rui Xie, Wei Ye, Jinan Sun +1

Code summaries are brief natural language descriptions of source code pieces. The main purpose of code summarization is to assist developers in understanding code and to reduce doc…

math.OC2019

Formation control for multiple agents with local measurements: continuous-time and sampled-data-based cases

Chen Wang, Shuai Li, Weiguo Xia +2

We study the formation control problem for a group of mobile agents in a plane, in which each agent is modeled as a kinematic point and can only use the local measurements in its l…

math.OC2018★ 2 cited

General formation control for multi-agent systems with double-integrator dynamics

Chen Wang, Weiguo Xia, Jinan Sun +2

We study the general formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or…

cs.LG2018

Deep Dynamic Boosted Forest

Haixin Wang, Xingzhang Ren, Jinan Sun +4

Random forest is widely exploited as an ensemble learning method. In many practical applications, however, there is still a significant challenge to learn from imbalanced data. To…