Papers by Zifan Xu
LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning (2024.findings-emnlp)
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| Challenge: | Existing methods require human experts or pre-trained LLMs to describe the skill to guide the selection. |
| Approach: | They propose a new approach that uses unsupervised learning to create a latent space representation of rationales with a variable called a reasoning skill. |
| Outcome: | Empirical results show that LaRS outperforms SOTA skill-based selection methods . it processes example banks four times faster and reduces LLM inferences by half . |