Summary of Towards Learning to Reason: Comparing Llms with Neuro-symbolic on Arithmetic Relations in Abstract Reasoning, by Michael Hersche et al.
Towards Learning to Reason: Comparing LLMs with Neuro-Symbolic on Arithmetic Relations in Abstract Reasoning
by Michael Hersche, Giacomo Camposampiero, Roger Wattenhofer, Abu Sebastian, Abbas Rahimi
First submitted to arxiv on: 7 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG); Symbolic Computation (cs.SC)
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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 This research compares large language models (LLMs) and neuro-symbolic approaches in solving Raven’s progressive matrices, a visual abstract reasoning test. The study uses textual prompts to measure the models’ abstract reasoning capabilities, finding that GPT-4 and Llama-3 70B struggle with arithmetic rules despite advanced prompting techniques. A neuro-symbolic approach, Abductive Rule Learner with Context-awareness (ARLC), is found to excel in understanding and executing arithmetic rules, achieving almost perfect accuracy on the test. The study also investigates the models’ ability to generalize to larger matrices and dynamic ranges, finding that LLMs struggle while ARLC maintains high accuracy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Raven’s progressive matrices are a visual test of abstract reasoning. Researchers compared two types of artificial intelligence (AI) models: large language models and neuro-symbolic approaches. They found that even with special help, the language models struggled to understand simple math rules. The neuro-symbolic approach did much better. The study also looked at how well these AI models can apply what they’ve learned to new situations. It turns out that the language models get confused when faced with more complex math problems, while the neuro-symbolic approach does a great job. |
Keywords
* Artificial intelligence * Gpt * Llama * Prompting
