Gonzalez, Joseph E.

Optimizing LLM Queries in Relational Data Analytics Workloads

Liu, S., Biswal, A., Kamsetty, A., Cheng, A., Schroeder, L. G., Patel, L., Cao, S., Mo, X., Stoica, I., Gonzalez, J. E., et al. (2024) · arXiv

Advanced Database Systems and QueriesTopic Modeling

Cited by 8

ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Scale

Jain, S., Zhang, X., Zhou, Y., Ananthanarayanan, G., Jiang, J., Shu, Y., & Gonzalez, J. (2018) · arXiv

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 5

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Patterson, D., Gonzalez, J., Hölzle, U., Le, Q. H., Liang, C., Munguia, L.-M., Rothchild, D., So, D., Texier, M., & Dean, J. (2022)

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 3

The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks

Cuadron, A., Li, D., Ma, W., Wang, X., Wang, Y., Zhuang, S., Liu, S., Schroeder, L. G., Xia, T., Mao, H., et al. (2025) · arXiv

Software Engineering ResearchAI-based Problem Solving and Planning

Cited by 2

Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First

Liu, S., Ponnapalli, S., Shankar, S., Zeighami, S., Zhu, A., Agarwal, S., Chen, R., Suwito, S., Yuan, S., Stoica, I., et al. (2025) · arXiv

Advanced Database Systems and QueriesScientific Computing and Data Management

Cited by 2

Specifications: The missing link to making the development of LLM systems an engineering discipline

Stoica, I., Zaharia, M., Gonzalez, J., Goldberg, K., Sen, K., Zhang, H., Angelopoulos, A., Patil, S. G., Chen, L., Chiang, W.-L., et al. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 2

Autellix: An Efficient Serving Engine for LLM Agents as General Programs

Luo, M., Shi, X., Cai, C., Zhang, T., Wong, J., Wang, Y., Wang, C., Huang, Y., Chen, Z., Gonzalez, J. E., et al. (2025) · arXiv

Cloud Computing and Resource ManagementParallel Computing and Optimization Techniques

Cited by 2

Search Arena: Analyzing Search-Augmented LLMs

Miroyan, M., Wu, T.-H., King, L., Li, T., Pan, J., Hu, X., Chiang, W.-L., Angelopoulos, A. N., Darrell, T., Norouzi, N., et al. (2025) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 1

How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models

Asawa, P., Zhu, A., O'Neill, A., Zaharia, M., Dimakis, A. G., & Gonzalez, J. E. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1

Sleep-time Compute: Beyond Inference Scaling at Test-time

Lin, K., Snell, C., Wang, Y., Packer, C., Wooders, S., Stoica, I., & Gonzalez, J. E. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies

Sundaresan, P., Grannen, J., Thananjeyan, B., Balakrishna, A., Ichnowski, J., Novoseller, E., Hwang, M., Laskey, M., Gonzalez, J. E., & Goldberg, K. (2021) · arXiv

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 0

SkyRL-Agent: Efficient RL Training for Multi-turn LLM Agent

Cao, S., Li, D., Zhao, F., Yuan, S., Hegde, S. R., Chen, C., Ruan, C., Griggs, T., Liu, S., Tang, E., et al. (2025) · arXiv

Software Engineering ResearchReinforcement Learning in Robotics

Cited by 0

vCache: Verified Semantic Prompt Caching

Schroeder, L. G., Desai, A., Cuadron, A., Chu, K., Liu, S., Zhao, M., Krusche, S., Kemper, A., Zaharia, M., & Gonzalez, J. E. (2025) · arXiv

Topic ModelingSoftware System Performance and Reliability

Cited by 0

VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models

Dunlap, L., Mandal, K., Darrell, T., Steinhardt, J., & Gonzalez, J. E. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Locality-aware Fair Scheduling in LLM Serving

Cao, S., Wang, Y., Mao, Z., Hsu, P.-L., Yin, L., Xia, T., Li, D., Liu, S., Zhang, Y., Zhou, Y., et al. (2025) · arXiv

Cloud Computing and Resource ManagementDistributed and Parallel Computing Systems

Cited by 0

LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Li, D., Cao, S., Griggs, T., Liu, S., Mo, X., Tang, E., Hegde, S., Hakhamaneshi, K., Patil, S. G., Zaharia, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0