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
6Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
No provider ID is stored.
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Yi-Ran Zhao (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Labor Markets: 1 paper
Claim outcomes
- Ai Safety And Ethics: 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 |
|---|---|---|---|
| Multi-agent LLM hiring systems can look fair at the outcome level while systematically subjecting certain candidates to greater scrutiny; a process-aware audit pipeline identifies career-gap, proxy and identity-triggered burdens and a targeted repair reduces procedural burden by over 70% while barely changing hire rates.arxiv | Yi-Ran Zhao unresolved |
2026-09-02 | 0 |
Citation observation summary
Semantic Scholar 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.