Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems

Tracking #: 883-1893

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Authors: 

Aniruddha Chattopadhyay
Raj Dandekar
Kaushik Roy

Responsible editor: 

Guest Editors NeSy 2025

Submission Type: 

Article in Special Issue (note in cover letter)

Full PDF Version: 

Cover Letter: 

Special Issue on NeSy 2025, Submission of extended conference or workshop papers We have updated my paper for journal submission, and we'd like to outline the key differences between the version we are submitting and the one we submitted to the NeSy 2025 conference. Expanded Scope and Deeper Analysis Our conference paper was a concise report of my initial research on metatuning for text-based reasoning. This journal submission represents a more complete and rigorous investigation. We've conducted new experiments that expand the scope of my original work, allowing us to provide a more thorough and nuanced analysis of the metatuning framework. New Experimental Findings and Contributions The journal submission includes new, more extensive findings that were not part of the conference paper. Specifically, we have: Tested metatuning with advanced prompting techniques. Our new experiments combine our original approach with Chain-of-Thought (COT) and self-reflection prompts. I found that while these methods significantly improve baseline performance, metatuning offers no further benefit and can even degrade accuracy in some cases. This is a major new insight into the limitations of our framework. Evaluated metatuning on a new domain. We extended our research to a video-based physical reasoning task using the CLEVRER dataset. Our results show that in this dynamic, visual domain, metatuning has a negligible effect on performance. This finding establishes important boundary conditions for our framework's effectiveness. Enhanced Rigor and Structure To meet the standards of a journal publication, We've structured this submission to provide a more detailed and robust account of our research. The paper now includes a more comprehensive literature review, a complete description of our new methodologies for all experiments, and a more in-depth discussion of our results. This journal version serves as a definitive record of our completed research, offering a more conclusive statement about the utility of metatuning approach.

Tags: 

  • Under Review