Papers by Sri Raghu Malireddi
LITE: Intent-based Task Representation Learning Using Weak Supervision (2022.naacl-main)
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| Challenge: | To-do texts are often short and under-specified, which poses a challenge for current text representation models. |
| Approach: | They propose a neural multi-task learning framework that extracts representations of English to-do tasks with a multi-head attention mechanism on top of a pre-trained text encoder. |
| Outcome: | The proposed model outperforms baseline models on four downstream tasks and achieves error reduction of 38.7%. |