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News/Semantic Interaction Information mediates compositional generalization in latent space
arxiv
PublishedApril 3, 2026 at 4:00 AM
—neutral

Semantic Interaction Information mediates compositional generalization in latent space

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2603.27134v2 Announce Type: replace Abstract: Are there still barriers to generalization once all relevant variables are known? We address this question via a framework that casts compositional generalization as a variational inference problem over latent variables with parametric interactions

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Discussion
Mentioned models
04
  • 01
    Recurrent Neural Networks (RNNs)
  • 02
    Echo State Networks
  • 03
    Fully Trained Networks
  • 04
    Representation Classification Chains (RCCs)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine learning#generalization#reinforcement learning#self-supervised learning

No replies yet. Be first.

Mentioned models
04
  • 01
    Recurrent Neural Networks (RNNs)
  • 02
    Echo State Networks
  • 03
    Fully Trained Networks
  • 04
    Representation Classification Chains (RCCs)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine learning#generalization#reinforcement learning#self-supervised learning

Related coverage

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arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning3harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning3harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models3harxivTemporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents3h
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