Revenge of the Fallen? Recurrent Models Match Transformers at Predicting Human Language Comprehension Metrics

30 April 2024

Papers citing "Revenge of the Fallen? Recurrent Models Match Transformers at Predicting Human Language Comprehension Metrics"

4 / 4 papers shown

Title
Frequency Explains the Inverse Correlation of Large Language Models' Size, Training Data Amount, and Surprisal's Fit to Reading Times Byung-Doh Oh Shisen Yue William Schuler 27 13 0 03 Feb 2024
Accounting for Agreement Phenomena in Sentence Comprehension with Transformer Language Models: Effects of Similarity-based Interference on Surprisal and Attention S. Ryu Richard L. Lewis 31 25 0 26 Apr 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 245 1,977 0 31 Dec 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 220 4,424 0 23 Jan 2020