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Found 9 papers, 2 papers with code
Large Language Model Augmented Exercise Retrieval for Personalized Language Learning
We study the problem of zero-shot exercise retrieval in the context of online language learning, to give learners the ability to explicitly request personalized exercises via natural language.
Local word statistics affect reading times independently of surprisal
Surprisal theory has provided a unifying framework for understanding many phenomena in sentence processing (Hale, 2001; Levy, 2008a), positing that a word's conditional probability given all prior context fully determines processing difficulty.
Simultaneous Translation and Paraphrase for Language Education
We present the task of Simultaneous Translation and Paraphrasing for Language Education (STAPLE).
Using LSTMs to Assess the Obligatoriness of Phonological Distinctive Features for Phonotactic Learning
To ascertain the importance of phonetic information in the form of phonological distinctive features for the purpose of segment-level phonotactic acquisition, we compare the performance of two recurrent neural network models of phonotactic learning: one that has access to distinctive features at the start of the learning process, and one that does not.
