3 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
Integrating Graph Neural Networks and Many-Body Expansion Theory for Potential Energy Surfaces
Siqi Chen, Zhiqiang Wang, Xianqi Deng +8
Rational design of next-generation functional materials relied on quantitative predictions of their electronic structures beyond single building blocks. First-principles quantum me…
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models
Xiao Liu, Lijun Zhang, Deepak Ganesan +1
Vision Language Models (VLMs) are central to Visual Question Answering (VQA) systems and are typically deployed in the cloud due to their high computational demands. However, this…
Assessing Simplification Levels in Neural Networks: The Impact of Hyperparameter Configurations on Complexity and Sensitivity
Huixin Guan
This paper presents an experimental study focused on understanding the simplification properties of neural networks under different hyperparameter configurations, specifically inve…
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models
Kunjal Panchal, Nisarg Parikh, Sunav Choudhary +3
Finetuning large language models (LLMs) in federated learning (FL) settings has become increasingly important as it allows resource-constrained devices to finetune a model using pr…
Attack-Resilient Image Watermarking Using Stable Diffusion
Lijun Zhang, Xiao Liu, Antoni Viros Martin +3
Watermarking images is critical for tracking image provenance and proving ownership. With the advent of generative models, such as stable diffusion, that can create fake but realis…