KRONE derives semantic execution hierarchies from flat logs to enable modular multi-level anomaly detection with hybrid local and nested-aware detectors plus limited LLM use, delivering 10% F1 gains and over 100x data efficiency on benchmarks and industrial data.
Hier- archical transformers for long document classification
2 Pith papers cite this work. Polarity classification is still indexing.
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MOGO introduces MoSA-VQ residual quantization and RQHC-Transformer for efficient real-time text-to-3D-motion generation with competitive quality on HumanML3D, KIT-ML and CMP.
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MOGO: Residual Quantized Hierarchical Causal Transformer for High-Quality and Real-Time 3D Human Motion Generation
MOGO introduces MoSA-VQ residual quantization and RQHC-Transformer for efficient real-time text-to-3D-motion generation with competitive quality on HumanML3D, KIT-ML and CMP.