Thesis Research Notes
This is a collection of notes and summaries from papers I reviewed as part of a systematic literature review for my undergraduate thesis in Computer Science.
The thesis explores a neuro-symbolic solution to the ARC-AGI benchmark, using lightweight language models and efficient symbolic representation techniques.
These notes aim to extract key insights and technical details relevant to intelligence, abstract reasoning, generalization, and neuro-symbolic AI.
For comments or suggestions, please reach out to me on LinkedIn or GitHub.