CORAL: Collaborative Automatic Labeling System based on Large Language Models
Summary: CORAL uses LLMs to generate coarse annotations, then trains compact SLMs via noisy-label/weak supervision to distill high-quality labels at scale and minimize manual effort. Includes statistical error detection, iterative LLM+SLM refinement with human corrections and a monitoring UI. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhen Zhu
- 2. Yibo Wang
- 3. Shouqing Yang
- 4. Lin Long
- 5. Runze Wu
- 6. Xiu Tang
- 7. Junbo Zhao
- 8. Haobo Wang
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,658 | LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation | 2025 | VLDB | 4.1945683e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,215 | Snuba: Automating Weak Supervision to Label Training Data | 2019 | VLDB | 0.0001323375 |
| 3,773 | Cleaning Crowdsourced Labels Using Oracles for Statistical Classification | 2019 | VLDB | 6.7758649e-05 |
| 5,282 | Deep Indexed Active Learning for Matching Heterogeneous Entity Representations | 2022 | VLDB | 5.5864206e-05 |
Previous
Page 1 / 1
Next