From Logs to Causal Inference: Diagnosing Large Systems
Summary: Applies causal inference to messy production logs via a log→table converter and two human-in-the-loop components: a Candidate Cause Ranker for fast cause hypotheses and an Interactive Causal Graph Refiner exploiting partial graphs. LOGos achieves 1.08–18× better precision for cause ranking, 1.61–16.83× fewer causal judgments, and a Log Converter with latency linear in log length, template variety, and variable-token fraction. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Markos Markakis
- 2. Brit Youngmann
- 3. Trinity Gao
- 4. Ziyu Zhang
- 5. Rana Shahout
- 6. Peter Baile Chen
- 7. Chunwei Liu
- 8. Ibrahim Sabek
- 9. Michael Cafarella
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,213 | Stress-Testing Causal Claims via Cardinality Repairs | 2026 | SIGMOD | 4.1945683e-05 |
| 10,581 | Causal DAG Summarization | 2025 | VLDB | 4.1945683e-05 |
| 10,658 | LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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