Topic
pre-training
Artificial Intelligence #lidar#self-supervised
HilDA: Hierarchical Distillation with Diffusion Advances Self-Supervised LiDAR Pre-Training
Researchers propose HilDA, a self-supervised pretraining framework for LiDAR backbones that uses hierarchical distillation and temporal occupancy diffusion. The method achieves state-of-the-art results on cross-modal distillation benchmarks for 3D object detection, scene flow, and semantic occupancy prediction.
Jun 21, 2026 1 source
Artificial Intelligence #llm#pre-training
From Detection to Recovery: Operational Analysis of LLM Pre-training on 504 NVIDIA B200 GPUs
A new paper presents an empirical operational analysis of a 504-GPU NVIDIA B200 cluster used for LLM pre-training. Analyzing 55 days of Prometheus metrics and 73 days of logs across 224 sessions, the study reveals that no single metric predicts all GPU failures, checkpoint I/O saturates NFS bandwidth, node failures are concentrated on a few systems, and automated retry chains achieve 33.3% success rate vs 12.5% manual.
Jun 16, 2026 1 source