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 →
2Distinct papers
103Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2336879588
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Yijun Wang (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 2 papers
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Organizational Efficiency: 2 papers
- Output Quality: 2 papers
- Other: 1 paper
- Task Allocation: 1 paper
- Decision Quality: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| MatrAIx simulates an 8.3 billion-person world to test AI products, releasing a 1M-person coreset and an interactive Playground to run thousands of simulated-user trials; controlled validation finds persona agents follow assigned behaviors in 91.5% of trials, though results rely heavily on LLM judges and grounded sources with known demographic skews.arxiv | Yijun Wang provider id |
2026-08-04 | 0 |
| A routing layer cuts ensemble LLM costs and delays: RouteMoA screens models with a cheap scorer and refines choices with lightweight judges, reducing inference cost by nearly 90% and latency by over 60% compared with conventional mixture-of-agents approaches.arxiv | Yijun Wang provider id |
2026-01-26 | 2 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.