GraphBit is a DAG-based engine-orchestrated framework for agentic LLMs that achieves 67.6% accuracy with zero hallucinations on GAIA benchmarks.
arXiv preprint arXiv:2101.07965 , year=
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DNG-Encoder represents NN weights as dynamic graphs to preserve sequential inference and powers INR2JLS, which raises INR classification accuracy by ~10% on CIFAR-100-INR.
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GraphBit: A Graph-based Agentic Framework for Non-Linear Agent Orchestration
GraphBit is a DAG-based engine-orchestrated framework for agentic LLMs that achieves 67.6% accuracy with zero hallucinations on GAIA benchmarks.
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Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space
DNG-Encoder represents NN weights as dynamic graphs to preserve sequential inference and powers INR2JLS, which raises INR classification accuracy by ~10% on CIFAR-100-INR.