#long-horizon-planning News & Analysis

3 articles tagged with #long-horizon-planning. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBearisharXiv – CS AI · Mar 267/10

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Can LLM Agents Be CFOs? A Benchmark for Resource Allocation in Dynamic Enterprise Environments

Researchers introduced EnterpriseArena, the first benchmark testing whether AI agents can function as CFOs by allocating resources in complex enterprise environments over 132 months. Testing on eleven advanced LLMs revealed poor performance, with only 16% of runs surviving the full simulation period, highlighting significant capability gaps in long-term resource allocation under uncertainty.

AIBullisharXiv – CS AI · Mar 267/10

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Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering

Researchers have developed ML-Master 2.0, an autonomous AI agent that achieves breakthrough performance in ultra-long-horizon machine learning tasks by using Hierarchical Cognitive Caching architecture. The system achieved a 56.44% medal rate on OpenAI's MLE-Bench, demonstrating the ability to maintain strategic coherence over experimental cycles spanning days or weeks.

🏢 OpenAI

AIBullisharXiv – CS AI · Mar 37/109

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HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents

Researchers introduce HiMAC, a hierarchical reinforcement learning framework that improves LLM agent performance on long-horizon tasks by separating macro-level planning from micro-level execution. The approach demonstrates state-of-the-art results across multiple environments, showing that structured hierarchy is more effective than simply scaling model size for complex agent tasks.