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
1Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2259534073
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Wenyu Wang (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Market Structure: 1 paper
- Error Rate: 1 paper
- Other: 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 |
|---|---|---|---|
| Decentralized price-learning commonly used in algorithmic pricing can push markets to a Conjectural Variations equilibrium driven by learning-induced bias; when firms see all rivals' prices or rival experiments are independent, the market instead converges to the standard Nash outcome. The paper proves convergence conditions and supplies finite-sample error bounds (≈T^{-1/2}).openalex | Wenyu Wang provider id |
2026-02-13 | 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.