Papers with explanations
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations (2022.acl-long)
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| Challenge: | Supervised learning has traditionally focused on inductive learning by looking at labeled examples of a task. |
| Approach: | They propose a benchmark for Classifier Learning Using natural language ExplanationS that provides natural language supervision over structured data and entailment-based models that learn from explanations. |
| Outcome: | The proposed model generalizes 18% better (relative) on novel tasks than a baseline that does not use explanations. |
Exploring the Effectiveness of Prompt Engineering for Legal Reasoning Tasks (2023.findings-acl)
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| Challenge: | Recent studies have shown that Chain-of-Thought (CoT) prompts improve tasks such as arithmetic and common-sense reasoning. |
| Approach: | They evaluate CoT prompts and various prompting strategies for legal reasoning tasks . they find that the best results are achieved with prompts derived from specific legal reasoning techniques . |
| Outcome: | The proposed approaches improve the COLIEE entailment task on the Japanese bar exam . the proposed approaches surpass the best system from 2022 with an accuracy of 0.789 . |