ArXiv TLDR

Shen Li

3 papers · Latest:

Machine Learning

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale

LoKA introduces a system-model co-design framework to make FP8 low-precision arithmetic practical and efficient for large recommendation models.

2605.10886
Computer Vision

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving

C-CoT uses VLMs and counterfactual chain-of-thought to improve safe autonomous driving decisions, especially in complex, high-risk scenarios.

2605.10744
Machine Learning

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost

FreeScale optimizes distributed training for sequence recommendation models, reducing computational bubbles by up to 90.3% on 256 H100 GPUs.

2604.24073

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