An LLM-driven evolutionary framework generates executable trading strategies as Python code and uses a meta-loop to evolve the prompts that guide synthesis.
James, and Nadia Polikarpova
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Large-scale analysis of AI bot PRs shows Copilot and Codex achieve the highest CI/CD success rates but more frequent AI contributions correlate with reduced workflow reliability.
Structured integration of LLMs in astronomy education, including a domain-specific tutor and documentation requirements, leads to improved AI literacy and reduced student reliance on AI over the semester.
citing papers explorer
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AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs
An LLM-driven evolutionary framework generates executable trading strategies as Python code and uses a meta-loop to evolve the prompts that guide synthesis.
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Reliability of AI Bots Footprints in GitHub Actions CI/CD Workflows
Large-scale analysis of AI bot PRs shows Copilot and Codex achieve the highest CI/CD success rates but more frequent AI contributions correlate with reduced workflow reliability.
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Teaching Astronomy with Large Language Models
Structured integration of LLMs in astronomy education, including a domain-specific tutor and documentation requirements, leads to improved AI literacy and reduced student reliance on AI over the semester.