Papers by Sreeparna Mukherjee
CUE Vectors: Modular Training of Language Models Conditioned on Diverse Contextual Signals (2022.findings-acl)
Copied to clipboard
| Challenge: | Using contextual universal embeddings, we train neural language models on one type of contextual data and adapts to novel context types. |
| Approach: | They propose a framework to modularize the training of neural language models that use diverse forms of context by eliminating the need to jointly train context and within-sentence encoders. |
| Outcome: | The proposed framework trains LMs on one type of contextual data and adapts to novel context types. |