VCR learns valid contextual representations for incomplete wearable signals via orthogonal disentanglement and missing-aware mixture-of-experts, improving robustness across full and missing-modality settings.
Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
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A new MoE training method integrates expert-level losses and partial online updates to improve forecasting accuracy and efficiency over standard statistical and neural models.
TeleGate achieves high-precision real-time whole-body teleoperation of humanoid robots by dynamically gating between expert policies and using a VAE motion prior to infer future intent from history, outperforming distillation baselines on dynamic motions with only 2.5 hours of mocap data.
Seed3D 2.0 advances 3D content generation via a coarse-to-fine geometry pipeline, unified PBR material model, and simulation-ready scene tools, reporting 69-89.9% win rates over commercial systems in human studies.
Few-shot prompting lifts F1 scores above 96 percent on electricity-invoice extraction for Gemini 1.5 Pro and Mistral-small, while hyperparameter changes produce only marginal gains.
citing papers explorer
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VCR: Learning Valid Contextual Representation for Incomplete Wearable Signals
VCR learns valid contextual representations for incomplete wearable signals via orthogonal disentanglement and missing-aware mixture-of-experts, improving robustness across full and missing-modality settings.
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Fast Training of Mixture-of-Experts for Time Series Forecasting via Expert Loss Integration
A new MoE training method integrates expert-level losses and partial online updates to improve forecasting accuracy and efficiency over standard statistical and neural models.
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TeleGate: Whole-Body Humanoid Teleoperation via Gated Expert Selection with Motion Prior
TeleGate achieves high-precision real-time whole-body teleoperation of humanoid robots by dynamically gating between expert policies and using a VAE motion prior to infer future intent from history, outperforming distillation baselines on dynamic motions with only 2.5 hours of mocap data.
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Seed3D 2.0: Advancing High-Fidelity Simulation-Ready 3D Content Generation
Seed3D 2.0 advances 3D content generation via a coarse-to-fine geometry pipeline, unified PBR material model, and simulation-ready scene tools, reporting 69-89.9% win rates over commercial systems in human studies.
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Information Extraction from Electricity Invoices with General-Purpose Large Language Models
Few-shot prompting lifts F1 scores above 96 percent on electricity-invoice extraction for Gemini 1.5 Pro and Mistral-small, while hyperparameter changes produce only marginal gains.