most citedTowards Efficient Large Language Model Serving: A Survey on System-Aware KV Cache Optimization

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cs.LG2026★ 2 cited

Towards Efficient Large Language Model Serving: A Survey on System-Aware KV Cache Optimization

Jiantong Jiang, Peiyu Yang, Rui Zhang +1

Despite the rapid advancements of large language models (LLMs), LLM serving systems remain memory-intensive and costly. The key-value (KV) cache, which stores KV tensors during aut…

cs.LG2026

MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions

Yuantong Li, Lei Yuan, Zhihao Zheng +27

Modern recommendation systems rank candidates by aggregating multiple behavioral signals through a value model. However, many commonly used signals are inherently affected by heter…

cs.LG2026

Attribution-Guided Model Rectification of Unreliable Neural Network Behaviors

Peiyu Yang, Naveed Akhtar, Jiantong Jiang +1

The performance of neural network models deteriorates due to their unreliable behavior on non-robust features of corrupted samples. Owing to their opaque nature, rectifying models…

cs.LG2024

Regulating Model Reliance on Non-Robust Features by Smoothing Input Marginal Density

Peiyu Yang, Naveed Akhtar, Mubarak Shah +1

Trustworthy machine learning necessitates meticulous regulation of model reliance on non-robust features. We propose a framework to delineate and regulate such features by attribut…

cs.LG2024

Fast-PGM: Fast Probabilistic Graphical Model Learning and Inference

Jiantong Jiang, Zeyi Wen, Peiyu Yang +2

Probabilistic graphical models (PGMs) serve as a powerful framework for modeling complex systems with uncertainty and extracting valuable insights from data. However, users face ch…