Publications

• Scalable and Accurate Application-level Crash-Consistency Testing via Representative Testing
  Yile Gu^*, Ian Neal^*, Jiexiao Xu, Shaun Christopher Lee, Ayman Said, Musa Haydar, Jacob Van Geffen, Rohan Kadekodi, Andrew Quinn, Baris Kasikci
  (To Appear) OOPSLA 2025, Singapore, October 2025. https://arxiv.org/abs/2503.01390
  
• Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models
  Keisuke Kamahori^*, Tian Tang^*, Yile Gu, Kan Zhu, Baris Kasikci
  (To Appear) ICLR 2025, Singapore, May 2025. https://arxiv.org/abs/2402.07033
  
• Perseus: Removing Energy Bloat from Large Model Training
  Jae-Won Chung, Yile Gu, Insu Jang, Luoxi Meng, Nikhil Bansal, Mosharaf Chowdhury
  SOSP 2024, Austin, TX, USA, November 2024. https://arxiv.org/abs/2312.06902
  
• Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models
  Yile Gu, Yifan Xiong, Jonathan Mace, Yuting Jiang, Yigong Hu, Baris Kasikci, Peng Cheng.
  https://arxiv.org/abs/2501.14170
  
• Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs
  Kan Zhu^*, Tian Tang^*, Qinyu Xu^*, Yile Gu, Zhichen Zeng, Rohan Kadekodi, Liangyu Zhao, Ang Li, Arvind Krishnamurthy, Baris Kasikci.
  https://arxiv.org/abs/2502.12216
  
• TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval
  Chien-Yu Lin^*, Keisuke Kamahori^*, Yiyu Liu, Xiaoxiang Shi, Madhav Kashyap, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Stephanie Wang, Arvind Krishnamurthy, Rohan Kadekodi, Luis Ceze, Baris Kasikci.
  https://arxiv.org/abs/2502.20969
  
• NanoFlow: Towards Optimal Large Language Model Serving Throughput
  Kan Zhu, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Yufei Gao, Qinyu Xu, Tian Tang, Zihao Ye, Keisuke Kamahori, Chien-Yu Lin, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci.
  https://arxiv.org/abs/2408.12757