Automatic Data Acquisition for Deep Learning
Summary: AutoData, an RL-guided system, automatically acquires training data from open ML benchmarks and data markets to support DL training. Its policy learns from AutoML feedback to guide high-quality data search; demonstrated on image classification and relational data prediction. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiabin Liu
- 2. Fu Zhu
- 3. Chengliang Chai
- 4. Yuyu Luo
- 5. Nan Tang
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,103 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.4460899e-05 |
| 5,386 | Selective Data Acquisition in the Wild for Model Charging | 2022 | VLDB | 5.5346315e-05 |
| 5,982 | Responsible Data Integration: Next-generation Challenges | 2022 | SIGMOD | 5.2409386e-05 |
| 7,180 | Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning | 2023 | VLDB | 4.8032775e-05 |
| 8,263 | Learned Data-aware Image Representations of Line Charts for Similarity Search | 2023 | SIGMOD | 4.5414364e-05 |
| 8,276 | Optimizing Data Acquisition to Enhance Machine Learning Performance | 2024 | VLDB | 4.5392079e-05 |
| 10,328 | LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning | 2026 | VLDB | 4.1905499e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 252 | Snorkel: Rapid Training Data Creation with Weak Supervision | 2018 | VLDB | 0.00030532082 |
| 1,179 | Table Union Search on Open Data | 2018 | VLDB | 0.00013458551 |
| 1,742 | Auctus: A Dataset Search Engine for Data Discovery and Augmentation | 2021 | VLDB | 0.00010695388 |
| 4,829 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 5.8890126e-05 |
| 5,369 | Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach | 2016 | SIGMOD | 5.5436995e-05 |
| 7,580 | Human-in-the-loop Outlier Detection | 2020 | SIGMOD | 4.7023767e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,306 | A Scalable AutoML Approach Based on Graph Neural Networks | 2022 | VLDB | 5.5725759e-05 |
| 1,992 | Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning | 2020 | SIGMOD | 9.8415851e-05 |
| 4,540 | Automating Exploratory Data Analysis via Machine Learning: An Overview | 2020 | SIGMOD | 6.0978937e-05 |
| 1,462 | ARDA: Automatic Relational Data Augmentation for Machine Learning | 2020 | VLDB | 0.00011866333 |
| 8,276 | Optimizing Data Acquisition to Enhance Machine Learning Performance | 2024 | VLDB | 4.5392079e-05 |
| 9,222 | Intelligent Agents for Data Exploration | 2024 | VLDB | 4.366098e-05 |
| 5,389 | Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search | 2021 | VLDB | 5.5339832e-05 |
| 10,958 | Data Acquisition for Improving Model Confidence | 2024 | SIGMOD | 4.1905499e-05 |
| 3,754 | Data Acquisition for Improving Machine Learning Models | 2021 | VLDB | 6.7830341e-05 |
| 5,386 | Selective Data Acquisition in the Wild for Model Charging | 2022 | VLDB | 5.5346315e-05 |