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2020 – today
- 2025
[i12]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:
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters! CoRR abs/2502.07374 (2025)- [i11]Shu Liu, Xiangxi Mo, Moshik Hershcovitch, Henric Zhang, Audrey Cheng, Guy Girmonsky, Gil Vernik, Michael Factor, Tiemo Bang, Soujanya Ponnapalli, Natacha Crooks, Joseph E. Gonzalez, Danny Harnik, Ion Stoica:
SkyStore: Cost-Optimized Object Storage Across Regions and Clouds. CoRR abs/2502.20818 (2025) - [i10]Chen Zhang, Kuntai Du, Shu Liu, Woosuk Kwon, Xiangxi Mo, Yufeng Wang, Xiaoxuan Liu, Kaichao You, Zhuohan Li, Mingsheng Long, Jidong Zhai, Joseph Gonzalez, Ion Stoica:
Jenga: Effective Memory Management for Serving LLM with Heterogeneity. CoRR abs/2503.18292 (2025) - 2024
- [c3]Sarah Wooders, Shu Liu, Paras Jain, Xiangxi Mo, Joseph E. Gonzalez, Vincent Liu, Ion Stoica:
Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud. NSDI 2024: 281-296 - [i9]Shu Liu, Asim Biswal, Audrey Cheng, Xiangxi Mo, Shiyi Cao, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia:
Optimizing LLM Queries in Relational Workloads. CoRR abs/2403.05821 (2024) - [i8]Xiaoxuan Liu, Cade Daniel, Langxiang Hu, Woosuk Kwon, Zhuohan Li, Xiangxi Mo, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang:
Optimizing Speculative Decoding for Serving Large Language Models Using Goodput. CoRR abs/2406.14066 (2024) - [i7]Yi Xu, Ziming Mao, Xiangxi Mo, Shu Liu, Ion Stoica:
Pie: Pooling CPU Memory for LLM Inference. CoRR abs/2411.09317 (2024) - 2023
- [j2]Sarah Wooders, Xiangxi Mo, Amit Narang, Kevin Lin, Ion Stoica, Joseph M. Hellerstein, Natacha Crooks
, Joseph E. Gonzalez:
RALF: Accuracy-Aware Scheduling for Feature Store Maintenance. Proc. VLDB Endow. 17(3): 563-576 (2023) - 2022
- [c2]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:
Context-Aware Streaming Perception in Dynamic Environments. ECCV (38) 2022: 621-638 - [i6]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:
Context-Aware Streaming Perception in Dynamic Environments. CoRR abs/2208.07479 (2022) - 2020
- [j1]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:
Towards Scalable Dataframe Systems. Proc. VLDB Endow. 13(11): 2033-2046 (2020) - [c1]Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov:
InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC 2020: 477-491 - [i5]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. CoRR abs/2001.00888 (2020)
2010 – 2019
- 2019
- [i4]Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica:
Dynamic Space-Time Scheduling for GPU Inference. CoRR abs/1901.00041 (2019) - [i3]Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica:
The OoO VLIW JIT Compiler for GPU Inference. CoRR abs/1901.10008 (2019) - [i2]Xiangxi Mo, Ruizhe Cheng, Tianyi Fang:
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning. CoRR abs/1906.04950 (2019) - 2018
- [i1]Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
InferLine: ML Inference Pipeline Composition Framework. CoRR abs/1812.01776 (2018)
Coauthor Index
aka: Joseph E. Gonzalez
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