Papers with neuron-level analysis method
Positional Artefacts Propagate Through Masked Language Model Embeddings (2021.acl-long)
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| Challenge: | Existing word embedding models have a uniform pitfall in assigning a static vector to a word type. |
| Approach: | They propose a neuron-level analysis method to investigate the source of this information by comparing outlier neurons within BERT and RoBERTa’s hidden state vectors. |
| Outcome: | The proposed method pre-trains the RoBERTa-based models and shows that the outliers disappear without positional embeddings. |