Summary of Break the Chain: Large Language Models Can Be Shortcut Reasoners, by Mengru Ding et al.
Break the Chain: Large Language Models Can be Shortcut Reasoners
by Mengru Ding, Hanmeng Liu, Zhizhang Fu, Jian Song, Wenbo Xie, Yue Zhang
First submitted to arxiv on: 4 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores Chain-of-Thought (CoT) reasoning, a complex module utilized in recent advancements. However, CoT methods face limitations in token consumption, applicability, and reproducibility. To address these challenges, the authors propose integrating human-like heuristics and shortcuts into language models (LMs) using “break the chain” strategies. These strategies disrupt traditional CoT processes by controlling variables to assess their effectiveness. The paper also develops zero-shot prompting strategies that encourage LMs to quickly exploit reasoning clues and bypass detailed procedural steps. Experiments across various LMs, both commercial and open-source, reveal effective performance with “break the chain” strategies. Additionally, the authors introduce ShortcutQA, a dataset designed to evaluate reasoning through shortcuts, compiled from competitive tests optimized for heuristic reasoning tasks like forward/backward reasoning and simplification. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about making AI systems better at thinking by giving them shortcuts to solve problems. It’s trying to fix some issues with how AI does this kind of thinking now. The authors are proposing new ways to help AI systems use these shortcuts, which will make them more efficient and effective. They tested their ideas on different AI models and found that they work well. They also created a special dataset called ShortcutQA that helps evaluate how well AI systems can use these shortcuts. |
Keywords
» Artificial intelligence » Prompting » Token » Zero shot
