4 papers
FidelityQ: Preserving Predictive Fidelity in Ultra-Low-Bit Language Model Quantization
Yujie Chen, Weiyan Zheng, Yiwu Yao +7
Ultra-low-bit scalar quantization offers a regular arithmetic structure for efficient deployment of large language models, but preserving predictive behavior at extreme precision r…
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…
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…
Toto: Time Series Optimized Transformer for Observability
Ben Cohen, Emaad Khwaja, Kan Wang +4
This technical report describes the Time Series Optimized Transformer for Observability (Toto), a new state of the art foundation model for time series forecasting developed by Dat…