72 citations · 87 across the 8 of their papers we have counts for
8 papers
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Yizhang Zhu, Liangwei Wang, Chenyu Yang +22
The rapid advancement of large language models (LLMs) has spurred the emergence of data agents, autonomous systems designed to orchestrate Data + AI ecosystems for tackling complex…
LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning
Xiaotian Lin, Yanlin Qi, Yizhang Zhu +4
Instruction tuning has emerged as a critical paradigm for improving the capabilities and alignment of large language models (LLMs). However, existing iterative model-aware data sel…
Harnessing Diversity for Important Data Selection in Pretraining Large Language Models
Chi Zhang, Huaping Zhong, Kuan Zhang +10
Data selection is of great significance in pre-training large language models, given the variation in quality within the large-scale available training corpora. To achieve this, re…
AutoCE: An Accurate and Efficient Model Advisor for Learned Cardinality Estimation
Jintao Zhang, Chao Zhang, Guoliang Li +1
Cardinality estimation (CE) plays a crucial role in many database-related tasks such as query generation, cost estimation, and join ordering. Lately, we have witnessed the emergenc…
PACE: Poisoning Attacks on Learned Cardinality Estimation
Jintao Zhang, Chao Zhang, Guoliang Li +1
Cardinality estimation (CE) plays a crucial role in database optimizer. We have witnessed the emergence of numerous learned CE models recently which can outperform traditional meth…
The Dawn of Natural Language to SQL: Are We Fully Ready?
Boyan Li, Yuyu Luo, Chengliang Chai +2
Translating users' natural language questions into SQL queries (i.e., NL2SQL) significantly lowers the barriers to accessing relational databases. The emergence of Large Language M…
Cost-Effective In-Context Learning for Entity Resolution: A Design Space Exploration
Meihao Fan, Xiaoyue Han, Ju Fan +4
Entity resolution (ER) is an important data integration task with a wide spectrum of applications. The state-of-the-art solutions on ER rely on pre-trained language models (PLMs),…
Crowd-Powered Data Mining
Chengliang Chai, Ju Fan, Guoliang Li +2
Many data mining tasks cannot be completely addressed by auto- mated processes, such as sentiment analysis and image classification. Crowdsourcing is an effective way to harness th…