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Holographic Memory Fails Zero-Shot Compositional Reasoning in Knowledge Graphs

Researchers have investigated the effectiveness of Holographic Reduced Representations (HRR) and Fourier HRR (FHRR) for zero-shot compositional reasoning in knowledge graphs. While these methods show promise and are competitive in predicting single-hop links, they fail to compose zero-shot queries. The study found that the primary bottleneck is not the binding or unbinding algebra or the cleanup mechanism, but rather the inherent difficulty in retrieving facts that are part of compositional chains due to capacity and interference effects within the superposed memory. AI

IMPACT Identifies a fundamental limitation in current knowledge graph embedding models for compositional reasoning, suggesting future research needs to focus on improving retrieval capacity under superposition.

RANK_REASON Academic paper detailing a mechanistic study of a specific AI technique's failure. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Holographic Memory Fails Zero-Shot Compositional Reasoning in Knowledge Graphs

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Academic paper detailing a mechanistic study of a specific AI technique's failure. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Randhir Kumar ·

    Holographic Memory for Zero-Shot Compositional Reasoning in Knowledge Graphs: A Mechanistic Study of Where and Why It Fails

    arXiv:2606.24948v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) models predict single-hop links well but have no mechanism for zero-shot compositional queries: multi-hop questions whose relation chains never appeared during training. Holographic Reduced Representa…