I am one of the authors—thank you for taking the time to go through and to summarise our paper!
About your question on the instructions vs inherent abilities:
Consider the scenario where we train a model on the task of Natural Language Inference, using a dataset like The Stanford Natural Language Inference (SNLI) Corpus. Suppose the model performs exceptionally well on this task. While we can now say that the model possesses the computational capability to excel in NLI, this doesn’t necessarily indicate that the model has developed inherent emergent reasoning abilities, especially those that it was not explicitly trained for while being trained on the SNLI corpus. For example, it is unlikely that our NLI-trained model will perform well in tasks that require logical reasoning skills.
I am one of the authors—thank you for taking the time to go through and to summarise our paper!
About your question on the instructions vs inherent abilities:
Consider the scenario where we train a model on the task of Natural Language Inference, using a dataset like The Stanford Natural Language Inference (SNLI) Corpus. Suppose the model performs exceptionally well on this task. While we can now say that the model possesses the computational capability to excel in NLI, this doesn’t necessarily indicate that the model has developed inherent emergent reasoning abilities, especially those that it was not explicitly trained for while being trained on the SNLI corpus. For example, it is unlikely that our NLI-trained model will perform well in tasks that require logical reasoning skills.
My 15 min talk on the paper might also help answer this question: https://www.youtube.com/live/I_38YKWzHR8?si=hWoUr4ucFrT8sFUi&t=3111
Just wanted to share that this work has now been peer-reviewed and accepted to ACL 2024.
arxiv has been updated with the published ACL version: https://arxiv.org/abs/2309.01809