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AutoPrune enables LLMs to autonomously design visual-token pruning strategies, achieving a remarkable 9.9x reduction in FLOPs without sacrificing performance.
Creative agents can now maintain context and evolve projects in real-time, transforming how we approach multimodal production.
A single misleading document can drastically reduce deep research agents' accuracy by up to 88%, exposing a critical vulnerability in their evidential reasoning capabilities.
Language corrections in PhysClaw-0 not only enhance robot autonomy but also boost success rates by over 35% while slashing human oversight time.
Forget solitary AI assistants; ClawNet envisions a future where your agent collaborates with *other people's* agents, securely and autonomously.
LLMs can now achieve better memory coherence and response fidelity thanks to MemFly's information bottleneck approach to on-the-fly memory optimization.
