Papers by Krishna Aswani
Auto-Evolve: Enhancing Large Language Model’s Performance via Self-Reasoning Framework (2024.findings-emnlp)
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Krishna Aswani, Huilin Lu, Pranav Patankar, Priya Dhalwani, Xue Tan, Jayant Ganeshmohan, Simon Lacasse
| Challenge: | Recent advances in prompt engineering strategies rely on static seed reasoning modules to simulate human approach to problem-solving. |
| Approach: | They propose a framework that enables LLMs to self-create dynamic reasoning modules and downstream action plan. |
| Outcome: | The proposed framework outperforms existing prompting strategies on a BigBench-Hard dataset and improves performance by 2.8% over existing methods. |