Papers by D. Anthony Bau
How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction (2021.emnlp-main)
Copied to clipboard
| Challenge: | Using RNN and transformer language models, we show consistent generalization in out-of-distribution contexts. |
| Approach: | They propose two idealized models of generalization in next-word prediction . they show that neural language models interpolate between these two forms of generalisation . |
| Outcome: | The proposed models exhibit consistent generalization in out-of-distribution contexts. |