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
3Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2300176172
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ruchir Puri (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Task Completion Time: 1 paper
- Innovation Output: 1 paper
- Organizational Efficiency: 1 paper
- Output Quality: 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 |
|---|---|---|---|
| Multiple general-purpose coding agents can dramatically accelerate hardware designs: a two-stage agent factory using up to 10 Claude Code agents achieves a mean 8.27× HLS speedup across 12 benchmarks, with peaks above 20×, and finds cross-kernel optimizations missed by per-subkernel search.arxiv | Ruchir Puri provider id |
2026-03-26 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.