Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models | Paper Citation Record

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Newton and the relation of mathematics to natural philosophy

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Guicciardini

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Newton, Maclaurin, and the authority of Mathematics

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Revisiting the mathematisation thesis: Galileo, Descartes, Newton, and the Language of Na- ture

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Using math in physics: Overview

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models The mathematization of economic theory

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models The general theory of relativity

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models What did mathematics do to physics?

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Unresolved cited work

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Fostering hooks and shifts: Tutorial tactics for guided mathematical discovery

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Naturalising mathematics? a wittgensteinian perspective

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models How a scientific discovery is made: A case history

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Stevens, V

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This paper cites AI and science: what 1,600 researchers think.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models AI and science: what 1,600 researchers think

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models On scientific understanding with artificial intelligence

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models AI and the transformation of social science research

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models From big data analysis to personalized medicine for all: challenges and opportunities

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Economics in the age of big data

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models AI meets physics: a comprehensive survey

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models The artificial intelligence revolution in digital finance in Saudi Arabia: A comprehensive review and proposed framework

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Fifth revolution: Applied AI & human intelligence with cyber physical systems

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models A survey on explainable artificial intelligence (xai): Toward medical xai

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Opening the black box: the promise and limitations of explainable machine learning in cardiology

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Opening the black box: interpretable machine learning for geneti- cists

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Meaningful explanations of black box AI decision systems

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Causability and explainability of artificial intelligence in medicine

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Interpretable scientific discovery with symbolic regression: a review

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Kronberger, B

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Symbolic regression in materials science

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Artificial intelligence in physical sciences: Symbolic re- gression trends and perspectives

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models AI Feynman: A physics-inspired method for symbolic regression

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Distilling Free-Form Natural Laws from Experimental Data

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Automated Rediscovery of the Maxwell Equations

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Discovering governing equations from data by sparse iden- tification of nonlinear dynamical systems

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Multi-objective symbolic regression for physics-aware dynamic modeling

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Toward physically plausible data-driven models: A novel neural network approach to symbolic regression

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Theory-guided data science: a new paradigm for scientific discovery from data

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models The rise of self-driving labs in chemical and materials sciences

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Towards robot scientists for autonomous scientific discovery

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Automatic discovery and optimization of chemical processes

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models On the issue of automation of processes during scientific research

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models BACON: A Production System That Discovers Empirical Laws

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Genetic programming as a means for programming computers by natural selection

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Functional genomic hypothesis generation and experimentation by a robot scientist

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Automated discovery systems, part 1: historical origins, main research programs, and method- ological foundations

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Toward an artificial intelligence physicist for unsupervised learning

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This paper cites Modeling hierarchy using symbolic regression.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Modeling hierarchy using symbolic regression

Reference 64

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Symbolic regression by exhaustive search: reducing the search space using syntactical constraints and efficient semantic structure deduplication

Reference 65

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models SymbolicGPT: A Generative Transformer Model for Symbolic Regression

Reference 66

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This paper cites Interpretable scientific discovery with symbolic regression: a review.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Interpretable scientific discovery with symbolic regression: a review

Reference 67

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Block building programming for symbolic regression

Reference 68

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Bayesian Symbolic Regression

Reference 69

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This paper cites A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge

Reference 71

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Unresolved cited work

Reference 72

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models The science of brute force

Reference 73

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Discovering governing equations from data by sparse iden- tification of nonlinear dynamical systems

Reference 74

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models PySINDy: A comprehensive Python package for robust sparse system identification

Reference 75

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Contemporary Symbolic Regression Methods and Their Relative Performance

Reference 76

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This paper cites Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients

Reference 77

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Where are we now?

Reference 78

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Improving model-based genetic pro- gramming for symbolic regression of small expressions

Reference 79

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Genetic Programming in Python, with a scikit-learn inspired API: gplearn

Reference 80

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models GSR: A Generalized Symbolic Regression Approach

Reference 81

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Observation b7c63cd8-dab9-41fa-a9b0-d7e77f7c7471 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models A Unified Framework for Deep Symbolic Regression

Reference 82

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Vertical Symbolic Regression via Deep Policy Gradient

Reference 83

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Observation 16e4b5a1-ac41-4c66-9b8f-91c41e07e21c · outbound

This paper cites A new formulation for symbolic regression to identify physico-chemical laws from experimental data.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models A new formulation for symbolic regression to identify physico-chemical laws from experimental data

Reference 84

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Observation 048059f8-54f9-4af4-b8f5-964f6e215eef · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

Reference 85

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Racing control variable genetic programming for symbolic regression

Reference 86

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Observation 4fd02e25-867a-4c16-8d01-475d8e2887f4 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Multi-objective symbolic regression for physics-aware dynamic modeling

Reference 87

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Observation 64aa1354-28c9-4f12-a736-60c18eec2e76 · outbound

This paper cites Symbolic regression for precision LHC physics.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Symbolic regression for precision LHC physics

Reference 88

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Observation 158c80b7-42ee-41a9-82d2-d0fa4f03d7bd · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Data-driven discovery of tsallis-like distribution using symbolic regression in high-energy physics

Reference 89

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Observation 225ff0f4-31c8-401a-b3e3-db346df50f4a · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Deep symbolic regression for physics guided by units con- straints: toward the automated discovery of physical laws

Reference 90

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Observation 837d6d9e-7c8f-4282-b27b-0711ffd4b4b1 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Ai feynman: a physics-inspired method for symbolic regression

Reference 91

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Observation 8f31e15d-851b-4103-9cbb-a452810736a9 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Physics-informed learning of governing equations from scarce data

Reference 92

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Extrapolation and learning equations

Reference 93

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Scalable Sparse Regression for Model Discovery: The Fast Lane to Insight

Reference 94

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Large language models are zero- shot rankers for recommender systems

Reference 95

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models A Survey on Large Language Models for Recommendation

Reference 96

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Recommender systems in the era of large language models (llms)

Reference 97

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Observation f756c714-bfd2-4a8f-afcd-b5667a34ea1b · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Decoding symbolism in language models

Reference 98

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Observation 958ed20f-66dd-49a0-bfb5-7de93968bd84 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Open-source solution for evaluation and benchmarking of large language models for public health

Reference 99

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Observation f2cff705-0fa9-4436-bee4-e18f21b3c1ea · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Applications of advanced natural language processing for clinical pharmacology

Reference 100

Resolution: verified exact; doi, observed 2026-08-15T16:37:34.841017Z

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Observation 2f4b7ca2-fc4f-44ba-a9bf-0c4689fd6964 · outbound

This paper cites Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System.

Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System

Reference 101

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Observation b4383a3a-5e21-4151-8a3a-bffef60a9607 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Once: Boosting content-based recommendation with both open- and closed-source large language models

Reference 102

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Observation a12fbab3-8256-409c-ac1d-d8d894a61f14 · outbound

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Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models Leveraging large language models for sequential recommendation

Reference 103

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