Xiangxi Mo

According to our database, Xiangxi Mo authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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, February, 2025

2024

Pie: Pooling CPU Memory for LLM Inference.

Yi Xu, Ziming Mao, Xiangxi Mo, Shu Liu, Ion Stoica

CoRR, 2024

Optimizing Speculative Decoding for Serving Large Language Models Using Goodput.

Xiaoxuan Liu, Cade Daniel, Langxiang Hu, Woosuk Kwon, Zhuohan Li, Xiangxi Mo, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang

CoRR, 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

Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud.

Sarah Wooders, Shu Liu, Paras Jain, Xiangxi Mo, Joseph E. Gonzalez, Vincent Liu, Ion Stoica

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

2023

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., November, 2023

2022

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, Bharathan Balaji, Joseph Gonzalez, Ion Stoica

Proceedings of the Computer Vision - ECCV 2022, 2022

2020

Towards Scalable Dataframe Systems.

Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran

Proc. VLDB Endow., 2020

InferLine: latency-aware provisioning and scaling for prediction serving pipelines.

Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov

Proceedings of the SoCC '20: ACM Symposium on Cloud Computing, 2020

2019

Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning.

Xiangxi Mo, Ruizhe Cheng, Tianyi Fang

CoRR, 2019

The OoO VLIW JIT Compiler for GPU Inference.

Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica

CoRR, 2019

Dynamic Space-Time Scheduling for GPU Inference.

Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica

CoRR, 2019

2018

InferLine: ML Inference Pipeline Composition Framework.

Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov

CoRR, 2018