What Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis

arXiv:2609.19212 · cs.AI · Submitted 2026-09-16 · Read on arXiv

cs.AI

Submitted: 2026-09-16

Updated: 2026-09-16

Comments: Preprint. Under review

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generalization — 58× in this paper · explained in 13 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Compositional Generalization — 5× in this paper · explained in 4 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Transformer Models — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Decoupling — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Baba Is AI: Break the Rules to Beat the Benchmark
• Reinforcement Learning for Compositional Generalization with Outcome-Level Optimization
• Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis

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