Humanoid-OmniOcc delivers a large-scale panoramic stereo occupancy dataset for humanoid robots via Real2Sim2Real, with a model that outperforms monocular baselines in both unseen sim scenes and real settings.
arXiv preprint arXiv:1908.00709 , year=
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An autonomous post-training system for a 30B model achieves near-top human performance on a reasoning leaderboard and revises its search policy after detecting that its dev metric had become misleading.
LLM agents iteratively generate and optimize data processing strategies for fine-tuning, delivering over 80% win rates versus unprocessed data and 65% versus LLM-based AutoML baselines while cutting search time by up to 10x.
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A-Evolve-Training: Autonomous Post-Training of a 30B Model
An autonomous post-training system for a 30B model achieves near-top human performance on a reasoning leaderboard and revises its search policy after detecting that its dev metric had become misleading.