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
3Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5076913086
ORCID evidence
Observed aliases (4)
- Niannian Yu (openalex, provider refresh)
- Niannian Yu (openalex, source metadata)
- Yu, Niannian (openalex, provider refresh)
- Yu, Niannian (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Task Completion Time: 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 AI system for financial reporting analysis reportedly cuts valuation errors by 19% and halves analysts' task time in a limited evaluation, though the paper provides few methodological details about datasets, baselines, and statistical robustness.openalex | Yu, Niannian provider id |
2026-08-24 | 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.