353 citations · 513 across the 7 of their papers we have counts for
5 papers · 1 filter
UserSumBench: A Benchmark Framework for Evaluating User Summarization Approaches
Chao Wang, Neo Wu, Lin Ning +5
Large language models (LLMs) have shown remarkable capabilities in generating user summaries from a long list of raw user activity data. These summaries capture essential user info…
Massively Scalable Inverse Reinforcement Learning in Google Maps
Matt Barnes, Matthew Abueg, Oliver F. Lange +5
Inverse reinforcement learning (IRL) offers a powerful and general framework for learning humans' latent preferences in route recommendation, yet no approach has successfully addre…
Smartphone-based Hard-braking Event Detection at Scale for Road Safety Services
Luyang Liu, David Racz, Kara Vaillancourt +9
Road crashes are the sixth leading cause of lost disability-adjusted life-years (DALYs) worldwide. One major challenge in traffic safety research is the sparsity of crashes, which…
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks
Amol Kapoor, Xue Ben, Luyang Liu +4
In this work, we examine a novel forecasting approach for COVID-19 case prediction that uses Graph Neural Networks and mobility data. In contrast to existing time series forecastin…
Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case
Neo Wu, Bradley Green, Xue Ben +1
In this paper, we present a new approach to time series forecasting. Time series data are prevalent in many scientific and engineering disciplines. Time series forecasting is a cru…