21 citations · 138 across the 53 of their papers we have counts for
9 papers · 1 filter
SaDiT: Efficient Protein Backbone Design via Latent Structural Tokenization and Diffusion Transformers
Shentong Mo, Lanqing Li
Generative models for de novo protein backbone design have achieved remarkable success in creating novel protein structures. However, these diffusion-based approaches remain comput…
MultiMed: Massively Multimodal and Multitask Medical Understanding
Shentong Mo, Paul Pu Liang
Biomedical data is inherently multimodal, consisting of electronic health records, medical imaging, digital pathology, genome sequencing, wearable sensors, and more. The applicatio…
IoT-LM: Large Multisensory Language Models for the Internet of Things
Shentong Mo, Russ Salakhutdinov, Louis-Philippe Morency +1
The Internet of Things (IoT) network integrating billions of smart physical devices embedded with sensors, software, and communication technologies is a critical and rapidly expand…
DailyMAE: Towards Pretraining Masked Autoencoders in One Day
Jiantao Wu, Shentong Mo, Sara Atito +3
Recently, masked image modeling (MIM), an important self-supervised learning (SSL) method, has drawn attention for its effectiveness in learning data representation from unlabeled…
MultiIoT: Benchmarking Machine Learning for the Internet of Things
Shentong Mo, Louis-Philippe Morency, Russ Salakhutdinov +1
The next generation of machine learning systems must be adept at perceiving and interacting with the physical world through a diverse array of sensory channels. Commonly referred t…
Variantional autoencoder with decremental information bottleneck for disentanglement
Jiantao Wu, Shentong Mo, Xiang Yang +4
One major challenge of disentanglement learning with variational autoencoders is the trade-off between disentanglement and reconstruction fidelity. Previous studies, which increase…
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan +6
Many real-world problems are inherently multimodal, from spoken language, gestures, and paralinguistics humans use to communicate, to force, proprioception, and visual sensors on r…
Learning by Examples Based on Multi-level Optimization
Shentong Mo, Pengtao Xie
Learning by examples, which learns to solve a new problem by looking into how similar problems are solved, is an effective learning method in human learning. When a student learns…
Automatic Speech Verification Spoofing Detection
Shentong Mo, Haofan Wang, Pinxu Ren +1
Automatic speech verification (ASV) is the technology to determine the identity of a person based on their voice. While being convenient for identity verification, we should aim fo…