4 citations · 4 across the 5 of their papers we have counts for
5 papers
X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference
Yixiao Zeng, Jianlei Zheng, Chaoda Zheng +10
Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Recent driving world models bui…
Understanding and Alleviating Memory Consumption in RLHF for LLMs
Jin Zhou, Hanmei Yang, Steven +4
Fine-tuning with Reinforcement Learning with Human Feedback (RLHF) is essential for aligning large language models (LLMs). However, RLHF often encounters significant memory challen…
Scaler: Efficient and Effective Cross Flow Analysis
Steven, Tang, Mingcan Xiang +4
Performance analysis is challenging as different components (e.g.,different libraries, and applications) of a complex system can interact with each other. However, few existing too…
AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
Mingcan Xiang, Steven Jiaxun Tang, Qizheng Yang +2
In the domain of multimedia and multimodal processing, the efficient handling of diverse data streams such as images, video, and sensor data is paramount. Model compression and mul…
ProTrain: Efficient LLM Training via Memory-Aware Techniques
Hanmei Yang, Jin Zhou, Yao Fu +4
Memory pressure has emerged as a dominant constraint in scaling the training of large language models (LLMs), particularly in resource-constrained environments. While modern framew…