most citedADVISE: AI-accelerated Design of Evidence Synthesis for Global Development

2 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

physics.flu-dyn2026

Label-Free Finite-Volume-Residual Training of Attention Graph Neural Networks for Coupled Thermo-Fluid Fields

Tianyu Li, Zhiwei Cao, Qingang Zhang +3

Neural surrogates are widely used in scientific machine learning for fast prediction of three-dimensional (3D) thermo-fluid fields. However, generating training data using conventi…

cs.CV2026

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

Xuerun Yan, Zhexi Lian, Nuoheng Zhang +5

Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition or suffer from fragmented world…

cs.LG2023

Drag-guided diffusion models for vehicle image generation

Nikos Arechiga, Frank Permenter, Binyang Song +1

Denoising diffusion models trained at web-scale have revolutionized image generation. The application of these tools to engineering design is an intriguing possibility, but is curr…

cs.LG2023

Multi-modal Machine Learning for Vehicle Rating Predictions Using Image, Text, and Parametric Data

Hanqi Su, Binyang Song, Faez Ahmed

Accurate vehicle rating prediction can facilitate designing and configuring good vehicles. This prediction allows vehicle designers and manufacturers to optimize and improve their…

cs.LG20231 cited

Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings

Binyang Song, Chenyang Yuan, Frank Permenter +2

Generative AI models have made significant progress in automating the creation of 3D shapes, which has the potential to transform car design. In engineering design and optimization…

cs.CL20232 cited

ADVISE: AI-accelerated Design of Evidence Synthesis for Global Development

Kristen M. Edwards, Binyang Song, Jaron Porciello +3

When designing evidence-based policies and programs, decision-makers must distill key information from a vast and rapidly growing literature base. Identifying relevant literature f…