Stoica, Ion

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Zheng, L., Chiang, W.-L., Sheng, Y., Li, T., Zhuang, S., Wu, Z., Zhuang, Y., Li, Z., Lin, Z., Xing, E. P., et al. (2023) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 27

Efficient LLM Scheduling by Learning to Rank

Fu, Y., Zhu, S., Su, R., Qiao, A., Stoica, I., & Zhang, H. (2024) · arXiv

Cloud Computing and Resource ManagementDistributed and Parallel Computing Systems

Cited by 21

RouteLLM: Learning to Route LLMs with Preference Data

Ong, I., Almahairi, A., Wu, V., Chiang, W.-L., Wu, T., Gonzalez, J. E., Kadous, M. W., & Stoica, I. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 15

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

Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems

Chen, L., Davis, J. Q., Hanin, B., Bailis, P., Stoica, I., Zaharia, M., & Zou, J. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 7

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Agrawal, L. A., Tan, S., Soylu, D., Ziems, N., Khare, R., Opsahl-Ong, K., Singhvi, A., Shandilya, H., Ryan, M. J., Jiang, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 7

JudgeBench: A Benchmark for Evaluating LLM-based Judges

Tan, S., Zhuang, S., Montgomery, K., Tang, W. Y., Cuadron, A., Wang, C., Popa, R. A., & Stoica, I. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

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

AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization

Cemri, M., Agrawal, S., Gupta, A., Liu, S., Cheng, A., Mang, Q., Naren, A., Erdogan, L. E., Sen, K., Zaharia, M., et al. (2026) · arXiv

Evolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms Research

Cited by 2

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

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

BlendServe: Optimizing Offline Inference with Resource-Aware Batching

Zhao, Y., Yang, S., Zhu, K., Zheng, L., Kasikci, B., Qiao, Y., Zhou, Y., Xing, J., & Stoica, I. (2026) · Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2

Cloud Computing and Resource ManagementParallel Computing and Optimization Techniques

Cited by 0

Establishing Best Practices in Building Rigorous Agentic Benchmarks

Zhu, Y., Jin, T., Pruksachatkun, Y., Zhang, A., Liu, S., Cui, S., Kapoor, S., Longpre, S., Meng, K., Weiss, R., et al. (2025) · Advances in Neural Information Processing Systems 38

Artificial Intelligence ApplicationsAI-based Problem Solving and Planning

Cited by 0

Prompt-to-Leaderboard

Frick, E., Chen, C., Tennyson, J., Li, T., Chiang, W.-L., Angelopoulos, A. N., & Stoica, I. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

LLM-as-a-Verifier: A General-Purpose Verification Framework

Kwok, J., Li, S., Atreya, P., Liu, Y., Jiang, Y., Finn, C., Pavone, M., Stoica, I., & Mirhoseini, A. (2026) · arXiv

Topic ModelingAI-based Problem Solving and Planning

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