3 papers
cs.CL2024
Exploring the Learning Capabilities of Language Models using LEVERWORLDS
Eitan Wagner, Amir Feder, Omri Abend
Learning a model of a stochastic setting often involves learning both general structure rules and specific properties of the instance. This paper investigates the interplay between…
cs.CL2024
CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models
Eitan Wagner, Yuli Slavutsky, Omri Abend
Although language model scores are often treated as probabilities, their reliability as probability estimators has mainly been studied through calibration, overlooking other aspect…
cs.CL2022
Topical Segmentation of Spoken Narratives: A Test Case on Holocaust Survivor Testimonies
Eitan Wagner, Renana Keydar, Amit Pinchevski +1
The task of topical segmentation is well studied, but previous work has mostly addressed it in the context of structured, well-defined segments, such as segmentation into paragraph…