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:
A5143450535
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Arunkumar Yadava (openalex, provider refresh)
- Arunkumar Yadava (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Output Quality: 1 paper
- Task Completion Time: 1 paper
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Regulatory Compliance: 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 |
|---|---|---|---|
| An LLM-powered agent framework cut wire transfer times by up to 40% and sped reimbursements by 82% in a 45-day bank pilot while cutting validation errors by more than 94%, but the findings come from a single-site pre/post trial with human oversight and limited controls.openalex | Arunkumar Yadava provider id |
2026-09-11 | 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.