Fundus-R1 is a fundus-reading MLLM trained exclusively on public data via RAG-generated reasoning traces and process-reward RLVR, outperforming its base model and a version trained without the traces.
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DeepStack introduces a fast performance model and hierarchical search method for co-optimizing 3D DRAM stacking, interconnects, and distributed scheduling in AI accelerators, delivering up to 9.5x throughput gains over baselines.
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Fundus-R1: Training a Fundus-Reading MLLM with Knowledge-Aware Reasoning on Public Data
Fundus-R1 is a fundus-reading MLLM trained exclusively on public data via RAG-generated reasoning traces and process-reward RLVR, outperforming its base model and a version trained without the traces.
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DeepStack: Scalable and Accurate Design Space Exploration for Distributed 3D-Stacked AI Accelerators
DeepStack introduces a fast performance model and hierarchical search method for co-optimizing 3D DRAM stacking, interconnects, and distributed scheduling in AI accelerators, delivering up to 9.5x throughput gains over baselines.