ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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The Unreasonable Effectiveness of Scaling Agents for Computer Use

📝 Summary:
Behavior Best-of-N bBoN improves computer-use agent reliability by generating multiple rollouts and selecting them via behavior narratives. This method achieves state-of-the-art performance on OSWorld and generalizes across operating systems, demonstrating effective CUA scaling.

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02250
• PDF: https://arxiv.org/pdf/2510.02250
• Project Page: https://www.simular.ai/articles/agent-s3
• Github: https://github.com/simular-ai/Agent-S

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For more data science resources:
https://t.iss.one/DataScienceT

#AIAgents #AIScaling #OperatingSystems #BehavioralAI #AIResearch
MemOS: A Memory OS for AI System

📝 Summary:
MemOS is a memory operating system that unifies plaintext, activation-based, and parameter-level memories for LLMs. It manages memory as a system resource with MemCubes, enabling efficient storage, retrieval, continual learning, and personalized modeling.

🔹 Publication Date: Published on Jul 4

🔹 Paper Links:
• arXiv Page: https://arxivexplained.com/papers/memos-a-memory-os-for-ai-system
• PDF: https://arxiv.org/pdf/2507.03724
• Project Page: https://memos.openmem.net/
• Github: https://github.com/MemTensor/MemOS

🔹 Models citing this paper:
https://huggingface.co/kagvi13/HMP

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For more data science resources:
https://t.iss.one/DataScienceT

#MemOS #LLMs #MemoryManagement #OperatingSystems #AI
Workload Schedulers -- Genesis, Algorithms and Differences

📝 Summary:
This paper categorizes modern workload schedulers into three classes: OS, Cluster, and Big Data. It details their evolution, algorithms, and differences. The conclusion highlights similarities in scheduling strategy design across both local and distributed systems.

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10258
• PDF: https://arxiv.org/pdf/2511.10258

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For more data science resources:
https://t.iss.one/DataScienceT

#WorkloadScheduling #OperatingSystems #DistributedComputing #SchedulingAlgorithms #ComputerScience