What Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis
Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to study rigorously under controlled settings. Existing studies therefore rely on simplifications such as elemental composition, productivity-based tests, and action-explicit goals, which make systematic generalization easier to study but omit some essential aspects of this capability. To characterize what these simplifications miss, we adopt a reasoning-centered lens and introduce TranSGrid, a testbed that brings deductive, inductive, and abductive reasoning together within a unified task. Experiments with seven Transformer models on 4,800 Tr...
| Authors | Chengwen Qi, Deheng Ye, Yatao Bian |
|---|---|
| Primary category | cs.AI |
| Published | 16 September 2026 |
| Last updated at source | 29 September 2026 |
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