Papers by Daphna Weinshall
The Grammar-Learning Trajectories of Neural Language Models (2022.acl-long)
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| Challenge: | In this paper, we show that neural language models with different initialization, architecture, and training data acquire linguistic phenomena in a similar order, despite their different end performance. |
| Approach: | They propose to use mutual inductive bias to study linguistic representations implicit in NLMs. |
| Outcome: | The proposed approach shows that NLMs with different initialization, architecture, and training data acquire linguistic phenomena in a similar order, despite their different end performance. |
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research (D18-1)
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| Challenge: | a prior art claim that sense-specific vectors provide an advantage over normal vectors is unfounded in two ways. |
| Approach: | They claim that sense-specific vectors provide an advantage over normal vectors due to the polysemy that they presumably represent. |
| Outcome: | The proposed results show that ground-truth polysemy degrades performance in word similarity tasks and that random assignment of words to senses improves performance. |