Drop a comment if you’ve worked on hybrid reasoning systems or want paper recommendations for a specific sub-area (e.g., neuro-symbolic VQA, program induction, or probabilistic logic learning).
NSAI is based on several key concepts:
Reasoning Accuracy under Distribution Shift . State-of-the-art NeSy models degrade only 5% vs. 45% for pure transformers. Drop a comment if you’ve worked on hybrid
Pure LLMs can’t reliably reason. Pure logic systems can’t perceive. The middle ground – neural perception + symbolic reasoning – is where AGI-level robustness lives. Drop a comment if you’ve worked on hybrid