Research map / Large language models / Language, safety and interpretability
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add intermediate sub-task labels to the input and train on the sub-task outputs as well as the final answer | Sequence-to-sequence learning of polynomial-time tasks · Tasks in P | zero-one loss | Helped |
| Add sub-task decomposition supervision | BERT-base Transformer · Bit-subset parity, 32 bits | validation accuracy | Helped |
| Train without intermediate sub-task supervision | BERT-base Transformer · Bit-subset parity, 32 bits | validation accuracy | Hurt |
| Remove intermediate sub-task supervision | Polynomial-time learnable task families under the stated hardness assumptions · Binary classification tasks | zero-one loss | Hurt |
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