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Found 5 papers, 3 papers with code
HHUplexity at Text Complexity DE Challenge 2022
In this paper, we describe our submission to the ‘Text Complexity DE Challenge 2022’ shared task on predicting the complexity of German sentences.
Multilingual Nonce Dependency Treebanks: Understanding how LLMs represent and process syntactic structure
We replicate the findings of M\"uller-Eberstein et al. (2022) on nonce test data and show that the performance declines on both MLMs and ALMs wrt.
Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building
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).
Probing for Constituency Structure in Neural Language Models
We find that 4 pretrained transfomer LMs obtain high performance on our probing tasks even on manipulated data, suggesting that semantic and syntactic knowledge in their representations can be separated and that constituency information is in fact learned by the LM.
