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Alvaro Bartolome PRO

alvarobartt

https://alvarobartt.me

AI & ML interests

machine learning @huggingface

Recent Activity

upvoted a paper about 6 hours ago

Granite Embedding Models

upvoted a collection 1 day ago

Phi-4

posted an update 3 days ago

🔥 Agents can do anything! @microsoft Research just announced the release of Magma 8B! Magma is a new Visual Language Model (VLM) with 8B parameters for multi-modal agents designed to handle complex interactions across virtual and real environments; and it's MIT licensed! Magma comes with exciting new features such as: - Introduces the Set-of-Mark and Trace-of-Mark techniques for fine-tuning - Leverages a large amount of unlabeled video data to learn the spatial-temporal grounding and planning - A strong generalization and ability to be fine-tuned for other agentic tasks - SOTA in different multi-modal benchmarks spanning across UI navigation, robotics manipulation, image / video understanding and spatial understanding and reasoning - Generates goal-driven visual plans and actions for agentic use cases Model: https://huggingface.co./microsoft/Magma-8B Technical Report: https://huggingface.co./papers/2502.13130

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alvarobartt's activity

upvoted a paper about 6 hours ago

Granite Embedding Models

Paper • 2502.20204 • Published 1 day ago • 3

upvoted a collection 1 day ago

Phi-4

Collection

Phi-4 family of small language and multi-modal models. • 7 items • Updated about 5 hours ago • 82

posted an update 3 days ago

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2600

🔥 Agents can do anything! @microsoft Research just announced the release of Magma 8B!

Magma is a new Visual Language Model (VLM) with 8B parameters for multi-modal agents designed to handle complex interactions across virtual and real environments; and it's MIT licensed!

Magma comes with exciting new features such as:
- Introduces the Set-of-Mark and Trace-of-Mark techniques for fine-tuning
- Leverages a large amount of unlabeled video data to learn the spatial-temporal grounding and planning
- A strong generalization and ability to be fine-tuned for other agentic tasks
- SOTA in different multi-modal benchmarks spanning across UI navigation, robotics manipulation, image / video understanding and spatial understanding and reasoning
- Generates goal-driven visual plans and actions for agentic use cases

Model: microsoft/Magma-8B
Technical Report: Magma: A Foundation Model for Multimodal AI Agents (2502.13130)