AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Existing auto-research benchmarks often entangle multiple sources of improvement, including training frameworks, hyperparameters, compute budgets, and data, making it difficult to attribute why one frontier agent outperforms another to specific research capabilities. In this work, we isolate and systematically evaluate...
This work proposes a comprehensive data-curation procedure that efficiently acquires rich medical knowledge data not only from medical imaging but also from extensive medical texts and general domain data and develops a medical-specialized MLLM, Lingshu-Med, which consistently outperforms existing multimodal baselines...
This work investigates the fundamental design principles required for robust visual text representation learning and trains Pixel Linguist II, a native-resolution vision encoder trained with on-the-fly rendering, unified contrastive grounding, and a multilingual curriculum over 280M training examples.
RadSight is proposed, a perception-driven MLLM built upon a dual 2D/3D encoder architecture that preserves native imaging spatial structures that achieves consistent improvements on public 2D and 3D medical benchmarks, further demonstrating that robust low-level visual perception is a critical foundation for reliable c...
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