Papers by Sheng-Fu Wang

2 papers
BLiMP: The Benchmark of Linguistic Minimal Pairs for English (2020.tacl-1)

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Challenge: Recent studies have examined how linguistic knowledge of language models (LMs) varies across English phenomena.
Approach: They propose a benchmark to evaluate linguistic knowledge of language models on major grammatical phenomena in English.
Outcome: The proposed benchmark evaluates the linguistic knowledge of language models on major grammatical phenomena in English.
Investigating BERT’s Knowledge of Language: Five Analysis Methods with NPIs (D19-1)

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Challenge: Recent work evaluating sentence representation models' knowledge of grammar has been slower to emerge.
Approach: They propose five experimental methods inspired by prior work evaluating pretrained sentence representation models to examine their grammatical knowledge.
Outcome: The proposed methods show that the model has significant knowledge of the licensing environment but its success varies widely across different methods.

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