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
10Unique collaborators
0/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2470870443
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Pei-Lun Zhou (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Consumer Welfare: 1 paper
- Other: 1 paper
- Ai Safety And Ethics: 1 paper
- Decision 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 |
|---|---|---|---|
| Meituan’s ATLAS framework diagnoses where multi-step AI assistants fail during execution and across subsequent turns, then uses calibrated diagnostic signals to optimize policies—live A/B tests on Meituan Xiaotuan report improved user engagement and downstream business outcomes.arxiv | Pei-Lun Zhou provider id |
2026-08-31 | Missing, not zero |
Citation observation summary
Semantic Scholar supplied counts for 0 of 1 papers in this view; 1 are missing.