Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
5Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2359217182
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Meng Zhang (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Error Rate: 1 paper
- Organizational Efficiency: 1 paper
- Adoption Rate: 1 paper
- Developer Productivity: 1 paper
- Task Completion Time: 1 paper
- Training Effectiveness: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Uber’s DragonCrawl uses GPT-4o to make mobile end-to-end tests far more robust and scalable, achieving roughly 92% pass rates across 1,013 CI tests while slashing test onboarding from about 100 hours to under 4 and claiming roughly 27 developer-years saved in maintenance.arxiv | Meng Zhang provider id |
2026-07-30 | 0 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.