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 →
2Distinct papers
3Unique collaborators
2/2Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2053888438
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ming Yin (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 2 papers
- Productivity: 2 papers
- Skills Training: 1 paper
Claim outcomes
- Decision Quality: 2 papers
- Automation Exposure: 1 paper
- Worker Satisfaction: 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 |
|---|---|---|---|
| An AI that challenges users’ reasoning improves judgment: when the system generates counterfactual critiques of human rationales, people rely less on the AI and make more accurate house-price predictions, though they report higher cognitive effort; the gains are strongest for participants comfortable with AI.semantic_scholar | Ming Yin provider id |
Fetched 2026-06-06 | 1 |
| An AI ensemble that alternates between a trust-building specialist and a performance-focused specialist improves human decision accuracy more than single-model assistants; a simple, provably near-optimal routing rule decides which specialist to use based on context.semantic_scholar | Ming Yin provider id |
Fetched 2026-03-17 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.