3 papers
cs.CY2026
The Hidden Cost of Thinking: Energy Use and Environmental Impact of LMs Beyond Pretraining
Jacob Morrison, Noah A. Smith, Emma Strubell
Modern language model development extends far beyond pretraining, yet environmental reporting remains narrowly focused on the cost of training a single final model. In this work, w…
cs.CL2024
Set the Clock: Temporal Alignment of Pretrained Language Models
Bowen Zhao, Zander Brumbaugh, Yizhong Wang +2
Language models (LMs) are trained on web text originating from many points in time and, in general, without any explicit temporal grounding. This work investigates the temporal cha…
cs.CL2024
Third-Party Language Model Performance Prediction from Instruction
Rahul Nadkarni, Yizhong Wang, Noah A. Smith
Language model-based instruction-following systems have lately shown increasing performance on many benchmark tasks, demonstrating the capability of adapting to a broad variety of…