3 citations · 4 across the 6 of their papers we have counts for
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cs.CL2023
Multilingual Nonce Dependency Treebanks: Understanding how Language Models represent and process syntactic structure
David Arps, Laura Kallmeyer, Younes Samih +1
We introduce SPUD (Semantically Perturbed Universal Dependencies), a framework for creating nonce treebanks for the multilingual Universal Dependencies (UD) corpora. SPUD data sati…
cs.CL2023★ 1 cited
Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building
Omar Momen, David Arps, Laura Kallmeyer
In this paper, we describe our submission to the BabyLM Challenge 2023 shared task on data-efficient language model (LM) pretraining (Warstadt et al., 2023). We train transformer-b…