arXiv AI
LegoSR: A Unified Framework for Self-improving Agent-Guided Scientific Discovery
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
arXiv AI
Jul 16
Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
arXiv:2605. 07323v2 Announce Type: replace Abstract: Discovering governing differential equations from observational data is a fundamental challenge in scientific machine learning.
Hugging Face Trending Papers
Jul 15
Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System
Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computational systems beyond data-fitting tools toward the generation and refinement of mechanistic models of the universe. Recent advances in symbolic regression (SR) and large-language-model (LLM)-based agents suggest that such systems can recover equations from data, incorporate domain priors, and automate parts of the research workflow.
arXiv AI
Jul 16
Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System
arXiv:2607. 13608v1 Announce Type: new Abstract: Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computational systems beyond data-fitting tools toward the generation and refinement of mechanistic models of the universe.
arXiv Machine Learning
Jun 9
Data-driven discovery of governing differential equations across physical systems
arXiv:2606. 09638v1 Announce Type: new Abstract: Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical phenomena.
arXiv AI
Oct 21
FoundPDE: A generative foundation model for data-driven symbolic discovery of partial differential equations
arXiv:2610.26963v1 Announce Type: cross Abstract: Discovering governing partial differential equations (PDEs) from observed data is a central inverse problem in computational science and engineering:...
arXiv Machine Learning
Jun 9
ERBench: A Benchmark and Testsuite for Equation Discovery Algorithms
arXiv:2606. 09276v1 Announce Type: new Abstract: Equation discovery aims to automate the discovery of scientific models in the form of mathematical equations from data.