PAGENT integrates static and dynamic program analysis guidance with an LLM agent to improve automated proof-of-concept generation success by 132% over prior agentic methods.
Codeact: Code adaptive compute-efficient tuning framework for code llms.arXiv preprint arXiv:2408.02193, 2024
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MOSAIC structures LLM-based model selection via memory-grounded blueprints and failure-aware RL, reporting gains in performance and traceability on financial time-series tasks over AutoML and agent baselines.
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Program Analysis Guided LLM Agent for Proof-of-Concept Generation
PAGENT integrates static and dynamic program analysis guidance with an LLM agent to improve automated proof-of-concept generation success by 132% over prior agentic methods.
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MOSAIC: Modular Orchestration for Structured Agentic Intelligence and Composition
MOSAIC structures LLM-based model selection via memory-grounded blueprints and failure-aware RL, reporting gains in performance and traceability on financial time-series tasks over AutoML and agent baselines.