Did You Read the Instructions? Rethinking the Effectiveness of Task Definitions in Instruction Learning (2023.acl-long)
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| Challenge: | Large language models have shown impressive performance in following natural language instructions to solve unseen tasks. |
| Approach: | They propose two strategies to help large language models better leverage task instructions . they propose to remove 60% of tokens from the task definitions while maintaining model performance . |
| Outcome: | The proposed approach achieves 4.2 Rouge-L improvement over 119 unseen test tasks. |
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Seyedali Mohammadi, Bhaskara Hanuma Vedula, Hemank Lamba, Edward Raff, Ponnurangam Kumaraguru, Francis Ferraro, Manas Gaur
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| Challenge: | Large Language Models (LLMs) have achieved remarkable success in aligning with user intentions. |
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| Challenge: | Recent studies have shown that instruction tuning can significantly vary depending on the task and format diversity of training data. |
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| Challenge: | Creating or annotating instances targeting specific functionalities is costly and further training models is expensive. |
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