Reliable & Scalable Synthetic Data for Physical AI (Part 1): Taming NVIDIA Cosmos with RoBoost Agent
Scaling Physical AI requires reliable synthetic data. Learn how RoBoost Agent integrates NVIDIA Cosmos to transform world models into trustworthy data engines for robotics and autonomous driving.
Vocabulary Trimming: An Easy and Effective Method for SLM Acceleration
Trimming large multilingual vocabularies in Small Language Models (SLM) is a simple, low-risk way to boost efficiency to its limit. It accelerates the model inference significantly while keeping accuracy almost unchanged.
GraLoRA: Boosting Fine-Tuning Accuracy Without Extra Cost
LoRA excels at efficient fine-tuning but suffers at higher ranks due to gradient entanglement. We introduce GraLoRA, which addresses these issues through finer-grained, block-wise updates, significantly enhancing performance and expressivity without overhead. GraLoRA outperforms LoRA across tasks, achieving up to +8.5% improvement in HumanEval+ Pass@1.
SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks
A brief review of the research paper from our team, published at ICML 2024.
Feb 17, 2025
Research