Fetching the paper…
Reading the bibliography…
Traditional Data+AI systems utilize data-driven techniques to optimize performance, but they rely heavily on human experts to orchestrate system pipelines, enabling them to adapt to changes in data, queries, tasks, and environments.
Ray: A Distributed Framework for Emerging AI Applications
P. Moritz, R. Nishihara, S. Wang, A. Tumanov, R. Liaw, et al · 2018
Earlier work this paper cites.
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
N. Reimers, I. Gurevych · 2019
Earlier work this paper cites.
Query performance prediction for concurrent queries using graph embedding
X. Zhou, J. Sun, G. Li, J. Feng · 2020
Earlier work this paper cites.
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
L. McInnes, J. Healy, J. Melville · 2020
Earlier work this paper cites.
AI meets database: AI4DB and DB4AI
G. Li, X. Zhou, L. Cao · 2021
Earlier work this paper cites.
Bao: Making learned query optimization practical
R. Marcus, P. Negi, H. Mao, N. Tatbul, M. Alizadeh, et al · 2021
Earlier work this paper cites.
A learned query rewrite system using monte carlo tree search
X. Zhou, G. Li, C. Chai, J. Feng · 2021
Earlier work this paper cites.
FACE: A normalizing flow based cardinality estimator
J. Wang, C. Chai, J. Liu, G. Li · 2021
Earlier work this paper cites.
Learned cardinality estimation: A design space exploration and a comparative evaluation
J. Sun, J. Zhang, Z. Sun, G. Li, N. Tang · 2021
Earlier work this paper cites.
Cost-based or learning-based? A hybrid query optimizer for query plan selection
X. Yu, C. Chai, G. Li, J. Liu · 2022
Earlier work this paper cites.
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction
B. Hilprecht and C. Binnig · 2022
Earlier work this paper cites.
Dynamic materialized view management using graph neural network
Y. Han, C. Chai, J. Liu, G. Li, C. Wei, et al · 2023
Earlier work this paper cites.
Grep: A graph learning based database partitioning system
X. Zhou, G. Li, J. Feng, L. Liu, W. Guo · 2023
Earlier work this paper cites.
Automatic database knob tuning: A survey
X. Zhao, X. Zhou, G. Li · 2023
Earlier work this paper cites.
Learned index: A comprehensive experimental evaluation
Z. Sun, X. Zhou, G. Li · 2023
Earlier work this paper cites.
In-database query optimization on SQL with ML predicates
C. Chai, J. Liu, N. Tang, J. Fan, D. Miao, et al · 2023
Cited alongside, same era.
SAGA: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications
S. Siddiqi, R. Kern, M. Boehm · 2023
Cited alongside, same era.
Febench: A benchmark for real-time relational data feature extraction
X. Zhou, C. Chen, K. Li, B. He, M. Lu, et al · 2023
Cited alongside, same era.
Automatic Database Index Tuning: A Survey
Y. Wu, X. Zhou, Y. Zhang, G. Li · 2024
Cited alongside, same era.
Breaking It Down: An In-Depth Study of Index Advisors
W. Zhou, C. Lin, X. Zhou, G. Li · 2024
Cited alongside, same era.
A. Hurst, A. Lerer, A. P. Goucher, A. Perelman, A. Ramesh, et al · 2024
In-database query optimization on SQL with ML predicates
Y. Guo, G. Li, R. Hu, Y. Wang · 2025
Closest in time.
Aop: Automated and interactive llm pipeline orchestration for answering complex queries
J. Wang, G. Li · 2025
Closest in time.
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
D. Guo, D. Yang, H. Zhang, J. Song, R. Zhang, et al · 2025
Closest in time.
Announcing the Agent2Agent Protocol (A2A)
R. Surapaneni, M. Jha, M. Vakoc, T. Segal · 2025
Closest in time.
DSBench: How Far Are Data Science Agents to Becoming Data Science Experts?
L. Jing, Z. Huang, X. Wang, W. Yao, W. Yu, et al · 2025
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Introducing the Model Context Protocol
Anthropic · 2024
Cited alongside, same era.
InfiAgent-DABench: evaluating agents on data analysis tasks
X. Hu, Z. Zhao, S. Wei, Z. Chai, Q. Ma, et al · 2024
Cited alongside, same era.
Metacognitive capabilities of llms: An exploration in mathematical problem solving
A. Didolkar, A. Goyal, N. R. Ke, S. Guo, M. Valko, T. Lillicrap, et al · 2024
Cited alongside, same era.
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
P. Sarthi, S. Abdullah, A. Tuli, S. Khanna, A. Goldie, et al · 2024
Cited alongside, same era.
Lost in the Middle: How Language Models Use Long Contexts
N. F. Liu, K. Lin, J. Hewitt, A. Paranjape, M. Bevilacqua, et al · 2024
Cited alongside, same era.
Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models
D. Yu, S. Kaur, A. Gupta, J. Brown-Cohen, A. Goyal, et al · 2024
Cited alongside, same era.
Z. Liu, P. Wang, R. Xu, S. Ma, C. Ruan, et al · 2025
Closest in time.
Vlm2vec: Training vision-language models for massive multimodal embedding tasks
Z. Jiang, R. Meng, X. Yang, S. Yavuz, Y. Zhou, et al · 2025
Closest in time.
Data Science Agent in Colab: The future of data analysis with Gemini
J. Fine, M. Kolla, I. Soloducho · 2025
Closest in time.
DatawiseAgent: A Notebook-Centric LLM Agent Framework for Automated Data Science
Z. You, Y. Zhang, D. Xu, Y. Lou, Y. Yan, et al · 2025
Closest in time.
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
P. Trirat, W. Jeong, Wonyong, S. J. Hwang · 2025
Closest in time.
Agent-Oriented Planning in Multi-Agent Systems
A. Li,Y. Xie, S. Li,F. Tsung, B. Ding, et al · 2025
Closest in time.
iDataLake: An LLM-Powered Analytics System on Data Lakes
J. Wang, G. Li, J. Feng · 2025
Closest in time.
D-Bot: An LLM-Powered DBA Copilot
Z. Sun, X. Zhou, J. Wu, W. Zhou, G. Li · 2025
Closest in time.
A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
L. Huang, W. Yu, W. Ma, W. Zhong, Z. Feng, et al · 2025
Closest in time.