15 citations · 24 across the 5 of their papers we have counts for
6 papers
On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models
William L. Tong, Aryo Lotfi, Emmanuel Abbe +6
State Space Models (SSMs) have emerged as a compelling alternative to Transformers, enabling sequence modeling with constant memory and linear compute. Although SSMs exhibit reason…
The Design Space of Tri-Modal Masked Diffusion Models
Louis Bethune, Victor Turrisi, Bruno Kacper Mlodozeniec +21
Discrete diffusion models have emerged as strong alternatives to autoregressive language models, with recent work initializing and fine-tuning a base unimodal model for bimodal gen…
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision
Wenxin Jiang, Vishnu Banna, Naveen Vivek +4
Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Dee…
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors
Vishnu Banna, Akhil Chinnakotla, Zhengxin Yan +7
Machine learning techniques are becoming a fundamental tool for scientific and engineering progress. These techniques are applied in contexts as diverse as astronomy and spam filte…
Analyzing Worldwide Social Distancing through Large-Scale Computer Vision
Isha Ghodgaonkar, Subhankar Chakraborty, Vishnu Banna +15
In order to contain the COVID-19 pandemic, countries around the world have introduced social distancing guidelines as public health interventions to reduce the spread of the diseas…
Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras
Isha Ghodgaonkar, Abhinav Goel, Fischer Bordwell +18
COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observin…