4 papers
Bullet Trains: Parallelizing Training of Temporally Precise Spiking Neural Networks
Todd Morrill, Christian Pehle, Anthony Zador
Continuous-time, event-native spiking neural networks (SNNs) operate strictly on spike events, treating spike timing and ordering as the representation rather than an artifact of t…
Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Heads
Todd Morrill, Aahlad Puli, Murad Megjhani +2
Deep mixture-of-experts models have attracted a lot of attention for survival analysis problems, particularly for their ability to cluster similar patients together. In practice, g…
Social Orientation: A New Feature for Dialogue Analysis
Todd Morrill, Zhaoyuan Deng, Yanda Chen +3
There are many settings where it is useful to predict and explain the success or failure of a dialogue. Circumplex theory from psychology models the social orientations (e.g., Warm…
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
Thomas P. Zollo, Todd Morrill, Zhun Deng +3
The recent explosion in the capabilities of large language models has led to a wave of interest in how best to prompt a model to perform a given task. While it may be tempting to s…