Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization | ScienceToStartup | ScienceToStartup

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References (42)

[1]

Agent Lightning: Train ANY AI Agents with Reinforcement Learning

2025Xufang Luo, Yuge Zhang et al.

[2]

RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents

2025Zijing Zhang, Ziyang Chen et al.

[3]

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"Develop EMPO$^2$, a hybrid framework enhancing LLM adaptation through memory-augmented exploration for complex task environments."

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Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization

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References (42)

Founder's Pitch

"Develop EMPO$^2$, a hybrid framework enhancing LLM adaptation through memory-augmented exploration for complex task environments."

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Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization

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References (42)

Founder's Pitch

"Develop EMPO$^2$, a hybrid framework enhancing LLM adaptation through memory-augmented exploration for complex task environments."

Commercial Viability Breakdown

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