84 citations · 85 across the 5 of their papers we have counts for
5 papers
LLM Agents for Time-Series: A Survey
Yilong Chen, Xiao Qin, Chenghao Liu +3
LLM-based agents are increasingly being developed for time-series problems, but their design choices vary substantially across task settings. This survey adopts a problem-driven ta…
DS-Instruct: Domain-Specific Data Synthesis for Large Language Models Instruction Tuning
Ruiyao Xu, Noelle I. Samia, Han Liu
Adapting Large Language Models (LLMs) to specialized domains requires high-quality instruction tuning datasets, which are expensive to create through human annotation. Existing dat…
SELDON: Supernova Explosions Learned by Deep ODE Networks
Jiezhong Wu, Jack O'Brien, Jennifer Li +6
The discovery rate of optical transients will explode to 10 million public alerts per night once the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, overw…
A Case Study in Model Failure? COVID-19 Daily Deaths and ICU Bed Utilisation Predictions in New York State
Vincent Chin, Noelle I. Samia, Roman Marchant +4
Forecasting models have been influential in shaping decision-making in the COVID-19 pandemic. However, there is concern that their predictions may have been misleading. Here, we di…
Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions
Roman Marchant, Noelle I. Samia, Ori Rosen +2
This paper provides a formal evaluation of the predictive performance of a model (and its various updates) developed by the Institute for Health Metrics and Evaluation (IHME) for p…