8 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.CL2024
Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
Dylan Zhang, Curt Tigges, Zory Zhang +3
This paper investigates the ability of transformer-based models to learn structural recursion from examples. Recursion is a universal concept in both natural and formal languages.…
cs.LG2023★ 8 cited
Linear Representations of Sentiment in Large Language Models
Curt Tigges, Oskar John Hollinsworth, Atticus Geiger +1
Sentiment is a pervasive feature in natural language text, yet it is an open question how sentiment is represented within Large Language Models (LLMs). In this study, we reveal tha…