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
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2366563206
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- N. Poungpeth (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Research Productivity: 1 paper
- Output Quality: 1 paper
- Skill Acquisition: 1 paper
- Training Effectiveness: 1 paper
- Consumer Welfare: 1 paper
- Governance And Regulation: 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 |
|---|---|---|---|
| Tailored AI coaching measurably improves how people express empathy: a randomized trial finds personalized LLM feedback produces more normatively empathic replies than generic training or no intervention. But identical messages lose perceived authenticity when recipients are told they came from AI, highlighting a trade-off between content quality and attribution.arxiv | N. Poungpeth provider id |
2026-03-16 | 3 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 3 cumulative citations. This is a coverage summary, not an author score or h-index.