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
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2316011291
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Yi Wu (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Adoption Rate: 1 paper
- Developer Productivity: 1 paper
- Innovation Output: 1 paper
- Output Quality: 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 |
|---|---|---|---|
| Autonomous Gemini-based agents can generate, train and deploy recommendation-model improvements at YouTube, reportedly speeding development and delivering successful production launches; evidence is promising but drawn from proprietary internal evaluations without transparent causal tests.arxiv | Yi Wu provider id |
2026-02-10 | 16 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 16 cumulative citations. This is a coverage summary, not an author score or h-index.