InferLine: ML Inference Pipeline Composition Framework. - Daniel Crankshaw; Gur-Eyal Sela; Corey Zumar; Xiangxi Mo; Joseph E. Gonzalez; Ion Stoica; Alexey Tumanov (CoRR, 2018)

Dynamic Space-Time Scheduling for GPU Inference. - Paras Jain 001; Xiangxi Mo; Ajay Jain; Harikaran Subbaraj; Rehan Sohail Durrani; Alexey Tumanov; Joseph Gonzalez 001; Ion Stoica (CoRR, 2019)

The OoO VLIW JIT Compiler for GPU Inference. - Paras Jain 001; Xiangxi Mo; Ajay Jain; Alexey Tumanov; Joseph E. Gonzalez; Ion Stoica (CoRR, 2019)

Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning. - Xiangxi Mo; Ruizhe Cheng; Tianyi Fang (CoRR, 2019)

InferLine: latency-aware provisioning and scaling for prediction serving pipelines. - Daniel Crankshaw; Gur-Eyal Sela; Xiangxi Mo; Corey Zumar; Ion Stoica; Joseph Gonzalez 001; Alexey Tumanov (SoCC, 2020)

Towards Scalable Dataframe Systems. - Devin Petersohn; William W. Ma; Doris Jung Lin Lee; Stephen Macke; Doris Xin; Xiangxi Mo; Joseph Gonzalez 001; Joseph M. Hellerstein; Anthony D. Joseph; Aditya G. Parameswaran (Proc. VLDB Endow., 2020)

Context-Aware Streaming Perception in Dynamic Environments. - Gur-Eyal Sela; Ionel Gog; Justin Wong; Kumar Krishna Agrawal; Xiangxi Mo; Sukrit Kalra; Peter Schafhalter; Eric Leong; Xin Wang 066; Bharathan Balaji; Joseph Gonzalez 001; Ion Stoica (ECCV (38), 2022)

RALF: Accuracy-Aware Scheduling for Feature Store Maintenance. - Sarah Wooders; Xiangxi Mo; Amit Narang; Kevin Lin; Ion Stoica; Joseph M. Hellerstein; Natacha Crooks; Joseph E. Gonzalez (Proc. VLDB Endow., 2023)

Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud. - Sarah Wooders; Shu Liu; Paras Jain 001; Xiangxi Mo; Joseph E. Gonzalez; Vincent Liu 001; Ion Stoica (NSDI, 2024)

Optimizing LLM Queries in Relational Workloads. - Shu Liu; Asim Biswal; Audrey Cheng; Xiangxi Mo; Shiyi Cao; Joseph E. Gonzalez; Ion Stoica; Matei Zaharia (CoRR, 2024)

Optimizing Speculative Decoding for Serving Large Language Models Using Goodput. - Xiaoxuan Liu; Cade Daniel; Langxiang Hu; Woosuk Kwon; Zhuohan Li 001; Xiangxi Mo; Alvin Cheung; Zhijie Deng; Ion Stoica; Hao Zhang 025 (CoRR, 2024)

Pie: Pooling CPU Memory for LLM Inference. - Yi Xu; Ziming Mao; Xiangxi Mo; Shu Liu; Ion Stoica (CoRR, 2024)

LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters! - Dacheng Li; Shiyi Cao; Tyler Griggs; Shu Liu; Xiangxi Mo; Eric Tang; Sumanth Hegde; Kourosh Hakhamaneshi; Shishir G. Patil; Matei Zaharia; Joseph E. Gonzalez; Ion Stoica (CoRR, 2025)

Jenga: Effective Memory Management for Serving LLM with Heterogeneity. - Chen Zhang 001; Kuntai Du; Shu Liu; Woosuk Kwon; Xiangxi Mo; Yufeng Wang; Xiaoxuan Liu; Kaichao You; Zhuohan Li 001; Mingsheng Long; Jidong Zhai; Joseph Gonzalez 001; et al. (CoRR, 2025)

SkyStore: Cost-Optimized Object Storage Across Regions and Clouds. - Shu Liu; Xiangxi Mo; Moshik Hershcovitch; Henric Zhang; Audrey Cheng; Guy Girmonsky; Gil Vernik; Michael Factor; Tiemo Bang; Soujanya Ponnapalli; Natacha Crooks; Joseph Gonzalez 001; et al. (Proc. VLDB Endow., 2025)