#in-context-learning2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago5

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Context and Diversity Matter: The Emergence of In-Context Learning in World Models

Researchers investigate in-context learning (ICL) in world models, identifying two core mechanisms - environment recognition and environment learning - that enable AI systems to adapt to new configurations. The study provides theoretical error bounds and empirical evidence showing that diverse environments and long context windows are crucial for developing self-adapting world models.

AINeutralarXiv – CS AI · 4h ago4

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Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures

Researchers conducted an in-depth analysis of in-context learning capabilities across different AI architectures including transformers, state-space models, and hybrid systems. The study reveals that while these models perform similarly on tasks, their internal mechanisms differ significantly, with function vectors playing key roles in self-attention and Mamba layers.