Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models (2024.emnlp-main)
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Nisarg Patel, Mohith Kulkarni, Mihir Parmar, Aashna Budhiraja, Mutsumi Nakamura, Neeraj Varshney, Chitta Baral
| Challenge: | Existing logical reasoning evaluation benchmarks focus on simplistic single-step or multi-step reasoning with limited set of inference rules. |
| Approach: | They propose to use a multi-step logical reasoning evaluation dataset to measure their ability for human-like multi- step logical thinking. |
| Outcome: | The proposed dataset covers three logic types including propositional, first-order, and non-monotonic logic with various inference rules and depths. |
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