3 papers
cs.LG2026
Toto 2.0: Time Series Forecasting Enters the Scaling Era
Emaad Khwaja, Chris Lettieri, Gerald Woo +10
We show that time series foundation models scale: a single training recipe produces reliable forecast-quality improvements from 4M to 2.5B parameters. We release Toto 2.0, a family…
cs.LG2026
ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response
Stephan Xie, Ben Cohen, Mononito Goswami +6
Time series question-answering (TSQA), in which we ask natural language questions to infer and reason about properties of time series, is a promising yet underexplored capability o…
cs.LG2025
This Time is Different: An Observability Perspective on Time Series Foundation Models
Ben Cohen, Emaad Khwaja, Youssef Doubli +16
We introduce Toto, a time series forecasting foundation model with 151 million parameters. Toto uses a modern decoder-only architecture coupled with architectural innovations desig…