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pro vyhledávání: '"Gauthier, Jon"'
Autor:
Gauthier, Jon
What are the mental and neural representations that drive language understanding and acquisition? This thesis presents a two-part suite of methods for addressing these questions, rooted in the idea that representational claims must jointly assert a c
Externí odkaz:
https://hdl.handle.net/1721.1/152560
Textless self-supervised speech models have grown in capabilities in recent years, but the nature of the linguistic information they encode has not yet been thoroughly examined. We evaluate the extent to which these models' learned representations al
Externí odkaz:
http://arxiv.org/abs/2306.06232
Autor:
Gauthier, Jon, Levy, Roger
Listeners recognize and integrate words in rapid and noisy everyday speech by combining expectations about upcoming content with incremental sensory evidence. We present a computational model of word recognition which formalizes this perceptual proce
Externí odkaz:
http://arxiv.org/abs/2305.13388
Autor:
Sinha, Koustuv, Gauthier, Jon, Mueller, Aaron, Misra, Kanishka, Fuentes, Keren, Levy, Roger, Williams, Adina
Targeted syntactic evaluations of language models ask whether models show stable preferences for syntactically acceptable content over minimal-pair unacceptable inputs. Most targeted syntactic evaluation datasets ask models to make these judgements w
Externí odkaz:
http://arxiv.org/abs/2212.08979
Human reading behavior is tuned to the statistics of natural language: the time it takes human subjects to read a word can be predicted from estimates of the word's probability in context. However, it remains an open question what computational archi
Externí odkaz:
http://arxiv.org/abs/2006.01912
While state-of-the-art neural network models continue to achieve lower perplexity scores on language modeling benchmarks, it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge. Further
Externí odkaz:
http://arxiv.org/abs/2005.03692
Autor:
Gauthier, Jon, Levy, Roger
What information from an act of sentence understanding is robustly represented in the human brain? We investigate this question by comparing sentence encoding models on a brain decoding task, where the sentence that an experimental participant has se
Externí odkaz:
http://arxiv.org/abs/1910.01244
Autor:
Gauthier, Jon, Ivanova, Anna
Language decoding studies have identified word representations which can be used to predict brain activity in response to novel words and sentences (Anderson et al., 2016; Pereira et al., 2018). The unspoken assumption of these studies is that, durin
Externí odkaz:
http://arxiv.org/abs/1806.00591
Children learning their first language face multiple problems of induction: how to learn the meanings of words, and how to build meaningful phrases from those words according to syntactic rules. We consider how children might solve these problems eff
Externí odkaz:
http://arxiv.org/abs/1805.04988
Autor:
Lucy, Li, Gauthier, Jon
Distributional word representation methods exploit word co-occurrences to build compact vector encodings of words. While these representations enjoy widespread use in modern natural language processing, it is unclear whether they accurately encode al
Externí odkaz:
http://arxiv.org/abs/1705.11168