2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2022★ 1 cited
Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns
Reto Gubelmann, Siegfried Handschuh
In this article, we explore the shallow heuristics used by transformer-based pre-trained language models (PLMs) that are fine-tuned for natural language inference (NLI). To do so,…
cs.CL2021★ 2 cited
Exploring the Promises of Transformer-Based LMs for the Representation of Normative Claims in the Legal Domain
Reto Gubelmann, Peter Hongler, Siegfried Handschuh
In this article, we explore the potential of transformer-based language models (LMs) to correctly represent normative statements in the legal domain, taking tax law as our use case…