Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models

23 September 2019

Papers citing "Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models"

9 / 9 papers shown

Title
Filtered Corpus Training (FiCT) Shows that Language Models can Generalize from Indirect Evidence Abhinav Patil Jaap Jumelet Yu Ying Chiu Andy Lapastora Peter Shen Lexie Wang Clevis Willrich Shane Steinert-Threlkeld 32 13 0 24 May 2024
SPAWNing Structural Priming Predictions from a Cognitively Motivated Parser Grusha Prasad Tal Linzen 19 4 0 11 Mar 2024
Structural Priming Demonstrates Abstract Grammatical Representations in Multilingual Language Models J. Michaelov Catherine Arnett Tyler A. Chang Benjamin Bergen 36 12 0 15 Nov 2023
Language model acceptability judgements are not always robust to context Koustuv Sinha Jon Gauthier Aaron Mueller Kanishka Misra Keren Fuentes R. Levy Adina Williams 21 17 0 18 Dec 2022
Collateral facilitation in humans and language models J. Michaelov Benjamin Bergen 17 11 0 09 Nov 2022
Neural reality of argument structure constructions Bai Li Zining Zhu Guillaume Thomas Frank Rudzicz Yang Xu 43 26 0 24 Feb 2022
Probing the phonetic and phonological knowledge of tones in Mandarin TTS models Jian Zhu 16 8 0 23 Dec 2019
The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models Noah Weber L. Shekhar Niranjan Balasubramanian 98 30 0 03 May 2018
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 201 882 0 03 May 2018