Next-Generation Evaluation Mechanisms for Reasoning-Based Artificial  Intelligence Models

Koushal Anitha Raja

Next-Generation Evaluation Mechanisms for Reasoning-Based Artificial Intelligence Models

Authors

Koushal Anitha Raja

Keywords:

Chain-Of-Thought Prompting, Reasoning Validation Systems, Cognitive Assessment Frameworks, Artificial General Intelligence Evaluation, Dynamic Performance Monitoring

Abstract

We introduce the TRIAD Framework (Trace, Robustness, Integrity, Adaptation, Dynamics), acomprehensive evaluation architecture for reasoning-based artificial intelligence models that addresses critical inadequacies in conventional accuracy-centric metrics

References

Jason Wei et al., "Chain-of-Thought Prompting Elicits Reasoning in Large Language Models," arXiv:2201.11903, 2023. Available: https://arxiv.org/abs/2201.11903

Jing Qian et al., "Limitations of Language Models in Arithmetic and Symbolic Induction," arXiv:2208.05051, 2022. Available: https://arxiv.org/abs/2208.05051

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Published

2026-01-16

How to Cite

Koushal Anitha Raja. (2026). Next-Generation Evaluation Mechanisms for Reasoning-Based Artificial Intelligence Models . Journal of Computational Analysis and Applications (JoCAAA), 35(1), 407–422. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4713