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cs.LG2025
RLHFSpec: Breaking the Efficiency Bottleneck in RLHF Training via Adaptive Drafting
Siqi Wang, Hailong Yang, Junjie Zhu +3
Reinforcement Learning from Human Feedback (RLHF) is an important fine-tuning technique for large language models (LLMs) and comprises three stages: generation, inference, and trai…
cs.LG2025
xGR: Efficient Generative Recommendation Serving at Scale
Qingxiao Sun, Tongxuan Liu, Shen Zhang +13
Recommendation system delivers substantial economic benefits by providing personalized predictions. Generative recommendation (GR) integrates LLMs to enhance the understanding of l…
cs.LG2024
Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities
Jiaxing Qi, Chang Zeng, Zhongzhi Luan +6
Log-based anomaly detection (LogAD) is the main component of Artificial Intelligence for IT Operations (AIOps), which can detect anomalous that occur during the system on-the-fly.…