@article{SmithVasishth2020,
  author    = {Smith, Garrett and Vasishth, Shravan},
  title     = {A principled approach to feature selection in models of sentence processing},
  series = {Cognitive science : a multidisciplinary journal of anthropology, artificial intelligence, education, linguistics, neuroscience, philosophy, psychology ; journal of the Cognitive Science Society},
  volume    = {44},
  journal   = {Cognitive science : a multidisciplinary journal of anthropology, artificial intelligence, education, linguistics, neuroscience, philosophy, psychology ; journal of the Cognitive Science Society},
  number    = {12},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0364-0213},
  doi       = {10.1111/cogs.12918},
  pages     = {25},
  year      = {2020},
  abstract  = {Among theories of human language comprehension, cue-based memory retrieval has proven to be a useful framework for understanding when and how processing difficulty arises in the resolution of long-distance dependencies. Most previous work in this area has assumed that very general retrieval cues like [+subject] or [+singular] do the work of identifying (and sometimes misidentifying) a retrieval target in order to establish a dependency between words. However, recent work suggests that general, handpicked retrieval cues like these may not be enough to explain illusions of plausibility (Cunnings \& Sturt, 2018), which can arise in sentences like The letter next to the porcelain plate shattered. Capturing such retrieval interference effects requires lexically specific features and retrieval cues, but handpicking the features is hard to do in a principled way and greatly increases modeler degrees of freedom. To remedy this, we use well-established word embedding methods for creating distributed lexical feature representations that encode information relevant for retrieval using distributed retrieval cue vectors. We show that the similarity between the feature and cue vectors (a measure of plausibility) predicts total reading times in Cunnings and Sturt's eye-tracking data. The features can easily be plugged into existing parsing models (including cue-based retrieval and self-organized parsing), putting very different models on more equal footing and facilitating future quantitative comparisons.},
  language  = {en}
}
@article{FelserCunningsBatterhametal.2012,
  author    = {Felser, Claudia and Cunnings, Ian and Batterham, Claire and Clahsen, Harald},
  title     = {The timing of Island effects in nonnative sentence processing},
  series = {Studies in second language acquisition},
  volume    = {34},
  journal   = {Studies in second language acquisition},
  number    = {1},
  publisher = {Cambridge University Press},
  address   = {Cambridge},
  issn      = {0272-2631},
  doi       = {10.1017/S0272263111000507},
  pages     = {67 -- 98},
  year      = {2012},
  abstract  = {Using the eye-movement monitoring technique in two reading comprehension experiments, this study investigated the timing of constraints on wh-dependencies (so-called island constraints) in first- and second-language (L1 and L2) sentence processing. The results show that both L1 and L2 speakers of English are sensitive to extraction islands during processing, suggesting that memory storage limitations affect L1 and L2 comprehenders in essentially the same way. Furthermore, these results show that the timing of island effects in L1 compared to L2 sentence comprehension is affected differently by the type of cue (semantic fit versus filled gaps) signaling whether dependency formation is possible at a potential gap site. Even though L1 English speakers showed immediate sensitivity to filled gaps but not to lack of semantic fit, proficient German-speaking learners of English as a L2 showed the opposite sensitivity pattern. This indicates that initial wh-dependency formation in L2 processing is based on semantic feature matching rather than being structurally mediated as in L1 comprehension.},
  language  = {en}
}