Description: System 2 Reasoning At Scale Workshop @ NeurIPS ---
System 2 Reasoning At Scale is a one-day workshop that focuses on improving reasoning in neural networks, particularly the challenges and strategies for achieving System-2 reasoning in transformer-like models. The workshop addresses issues like distinguishing memorization from rule-based learning, understanding, syntactic generalization, and compositionality. The workshop also covers the importance of understanding how systematic models are in their decisions for AI safety, integrating neural networks with
The authors are welcome to submit a 4-page or 8-page (short/long) paper based on in-progress work, or a relevant paper being presented at the main conference, that aims to answer the following questions:
What do we need to imbue language models with System-2 reasoning capabilities? Do we need this kind of capability? Are scale and the “bitter lesson” going to dictate how the future of AI technology will unfold? Do we need a different mechanism for implementing System-2 reasoning, or should it be a property that emerges from a possibly different training method? Where should a system like this be implemented? Implicitly inside the model, or explicitly in some engineered system around the model, like search o