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
10Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2269474675
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Kaiyu Li (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Research Productivity: 1 paper
- Adoption Rate: 1 paper
- Developer Productivity: 1 paper
- Other: 1 paper
- Output Quality: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| Agentic research assistants fall short: on AARRI-Bench the best-performing agent configuration succeeds on just 68.3% of granular researcher tasks and frequently overlooks subtle but critical judgments, suggesting current systems cannot fully replace human researchers.arxiv | Kaiyu Li provider id |
2026-06-05 | 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.