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20242026
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cs.AI2025

Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowledge via Abductive Inference with AI-Noether

Karan Srivastava, Sanjeeb Dash, Ryan Cory-Wright +3

Advances in AI have shown great potential in contributing to the acceleration of scientific discovery. Symbolic regression can fit interpretable models to data, but these models ar…

cs.AI2025

The Need for Verification in AI-Driven Scientific Discovery

Cristina Cornelio, Takuya Ito, Ryan Cory-Wright +2

Artificial intelligence (AI) is transforming the practice of science. Machine learning and large language models (LLMs) can generate hypotheses at a scale and speed far exceeding t…

cs.AI2025

Language Models Coupled with Metacognition Can Outperform Reasoning Models

Vedant Khandelwal, Francesca Rossi, Keerthiram Murugesan +4

Large language models (LLMs) excel in speed and adaptability across various reasoning tasks, but they often struggle when strict logic or constraint enforcement is required. In con…

cs.AI2025

Quantifying artificial intelligence through algorithmic generalization

Takuya Ito, Murray Campbell, Lior Horesh +2

The rapid development of artificial intelligence (AI) systems has created an urgent need for their scientific quantification. While their fluency across a variety of domains is imp…

cs.AI2024

Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI Hilbert

Ryan Cory-Wright, Cristina Cornelio, Sanjeeb Dash +2

The discovery of scientific formulae that parsimoniously explain natural phenomena and align with existing background theory is a key goal in science. Historically, scientists have…