On the LLM Verification for Argument Graph Generation
Multi-agent LLM systems can formalize natural-language argumentation end-to-end, turning plain text into structured graphs by classifying components, connecting them with relations, and enriching the resulting graphs into formal models.
ProofPaper ↗
Key points
- Quality assurance for those graphs is almost always another LLMs: a reviewer, judge, or critic agent.
- In this work, we argue that in argument graph verification, the allocation should be similar, and based on what each instrument can guarantee.
- We propose layered verification: starting from deterministic checks, moving to solver-based and LLM reviews, and utilizing debate only under uncertainty, leaving human judgment for what no other instrument can decide.
- We ground our principle with a study on human-annotated graphs with injected structural defects.
Sources (1)
- [1]On the LLM Verification for Argument Graph GenerationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 10:41 PM
Multi-agent LLM systems can formalize natural-language argumentation end-to-end, turning plain text into structured graphs by classifying components, connecting them with relations, and enriching the resulting graphs into formal models.
Quality assurance for those graphs is almost always another LLMs: a reviewer, judge, or critic agent.
Extractive summary: sentences quoted from the sources.
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