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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5100334733
ORCID evidence
Observed aliases (2)
- Yuan Yuan (openalex, provider refresh)
- Yuan Yuan (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
Claim outcomes
- Output Quality: 1 paper
- Organizational Efficiency: 1 paper
- Governance And Regulation: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| A multimodal graph-transformer system sharply raises firm-level risk-detection accuracy to 94.1% on Chinese A-share documents and trains in 14 minutes, outperforming tree and graph baselines; the approach promises faster, cheaper risk analytics but its benefits likely hinge on access to similarly rich, jurisdiction-specific BFLT data.openalex | Yuan Yuan provider id |
2026-08-04 | 0 |
Citation observation summary
OpenAlex 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.