SCiL 2022: all accepted papers
- ANLIzing the Adversarial Natural Language Inference DatasetAdina Williams, Tristan Thrush, Douwe Kielaour summary
- Analysis of Language Change in Collaborative Instruction Following ↗Anna Effenberger, Eva Yan, Rhia Singh et al.
- Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructionsSoo-Hwan Lee, Sebastian Schusterour summary
- Evaluating Structural Economy Claims in Relative Clause Attachment ↗Aniello De Santo, So Young Lee
- Horse or pony? Visual typicality and lexical frequency affect variability in object naming ↗Eleonora Gualdoni, Andreas Madebach, Thomas Brochhagen et al.
- How well do LSTM language models learn filler-gap dependencies? ↗Satoru Ozaki, Dan Yurovsky, Lori Levin
- Learning Argument Structures with Recurrent Neural Network Grammars ↗Ryo Yoshida, Yohei Oseki
- Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives ↗Alex Shilen, Colin Wilson
- Learning Stress Patterns with a Sequence-to-Sequence Neural Network ↗Brandon Prickett, Joe Pater
- Learning constraints on wh-dependencies by learning how to efficiently represent wh-dependencies: A developmental modeling investigation with Fragment Grammars ↗Niels Dickson, Lisa Pearl, Richard Futrell
- Linguistic Complexity and Planning Effects on Word Duration in Hindi Read Aloud Speech ↗Sidharth Ranjan, Rajakrishnan Rajkumar, Sumeet Agarwal
- Masked language models directly encode linguistic uncertainty ↗Cassandra L. Jacobs, Ryan J. Hubbard, Kara D. Federmeier
- Parsing Early Modern English for Linguistic SearchSeth Kulick, Neville Ryant, Beatrice Santoriniour summary
- Remodelling complement coercion interpretation ↗Frederick Gietz, Barend Beekhuizen
- The interaction between cognitive ease and informativeness shapes the lexicons of natural languages ↗Thomas Brochhagen, Gemma Boleda
- Universal Dependencies and Semantics for English and Hebrew Child-directed SpeechIda Szubert, Omri Abend, Nathan Schneider et al.our summary
- When classifying arguments, BERT doesn't care about word order...except when it matters ↗Isabel Papadimitriou, Richard Futrell, Kyle Mahowald
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