Papers by Sungjun Han
Towards Understanding the Relationship between In-context Learning and Compositional Generalization (2024.lrec-main)
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| Challenge: | In-context learning is an inductive bias for compositional generalization, but many deep neural architectures struggle with this ability. |
| Approach: | They propose to force a causal Transformer to in-context learn to promote compositional generalization by using earlier examples to generalize to later ones. |
| Outcome: | The proposed model can solve 'ordinary' learning problems by utilizing earlier examples to generalize to later ones, i.e., in-context learning. |