Derived from arXiv:2607.17917 - PEARL: Auditable Repair for Scientific Reasoning Graph Extraction
Scanned 9/11/2026
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# PEARL: Auditable Repair for Scientific Reasoning Graph Extraction
Derived from arXiv:2607.17917 - PEARL: Auditable Repair for Scientific Reasoning Graph Extraction
## Core Concept
Scientific Reasoning Graph Extraction (SRGE) aims to recover explicit links among observations, evidence, intermediate claims, and paper-level conclusions. LLMs can produce graph-like scientific explanations, but their outputs often mix malformed syntax, drifting edge labels, incorrectly oriented roots, and weak source anchors. We propose PEARL (Peircean Extraction via Abstraction and Repair Layer), a training-free framework that turns noisy LLM graph responses into auditable reasoning graphs an...
## Key Insights
- Derived from arXiv:2607.17917
- Published: 2026-07-20
- Utility Score: 1.00
- Authors: Bohan Su, Pengze Li, Yuchen Lu et al.
## Activation
pearl-auditable-repair-for-scientific-reasoning-gr, 2607.17917
## References
- arXiv: https://arxiv.org/abs/2607.17917
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