Graph of States: Solving Abductive Tasks with Large Language Models
Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former two, abductive reasoning remains significantly underexplored. Existing frameworks, predominantly designed for static deductive tasks, fail to generalize to abductive reasoning due to unstructured state representation and lack of explicit state control. Consequently, they are inevitably prone to Evidence Fabrication, Context Drift, Failed Backtracking, and Early Stopping. To bridge this gap, we introduce Graph of States (GoS), a general-purpose neuro-symbolic framework tailored for abductive tasks. GoS grounds multi-agent collaboration in a str...
| Authors | Yu Luo, Rongchen Gao, Lu Teng et al. |
|---|---|
| Primary category | cs.AI |
| Published | 22 March 2026 |
| Last updated at source | 14 May 2026 |
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