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HPSD enables TI2V models to internalize high-quality visual cues, resulting in a remarkable boost in text-to-video performance while simultaneously enhancing image-to-video generation.
Intern-S2-Preview-397B not only excels in multimodal scientific reasoning but also enhances biological instruction performance without altering its foundational architecture.
Achieving 93.02% accuracy in molecular structure recognition, MinerU.Chem outperforms existing systems, unlocking new possibilities for AI-driven chemistry research.
Achieving trillion-parameter performance with just 35 billion parameters by scaling agent horizons reveals a new frontier in model efficiency.
ThoughtFold cuts token usage by 56% without sacrificing accuracy by folding reasoning chains and eliminating redundant explorations.
Forget bigger models: massive gains in document parsing accuracy are still possible through smarter data engineering alone.
