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1
Incorporating Residual and Normalization Layers into Analysis of Masked Language Models ...
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Topicalization in Language Models: A Case Study on Japanese ...
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Lower Perplexity is Not Always Human-Like ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.405 Abstract: In computational psycholinguistics, various language models have been evaluated against human reading behavior (e.g., eye movement) to build human-like computational models. However, most previous efforts have focused almost exclusively on English, despite the recent trend towards linguistic universal within the general community. In order to fill the gap, this paper investigates whether the established results in computational psycholinguistics can be generalized across languages. Specifically, we re-examine an established generalization ---\textit{the lower perplexity a language model has, the more human-like the language model is}--- in Japanese with typologically different structures from English. Our experiments demonstrate that this established generalization exhibits a surprising lack of universality; namely, lower perplexity is not always human-like. Moreover, this discrepancy between English and Japanese is further explored from ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25824-lower-perplexity-is-not-always-human-like
https://dx.doi.org/10.48448/mjnr-8446
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Lower Perplexity is Not Always Human-Like ...
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5
Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese ...
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6
Attention is Not Only a Weight: Analyzing Transformers with Vector Norms ...
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7
Modeling Event Salience in Narratives via Barthes' Cardinal Functions ...
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