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Peak-Then-Collapse and the Four Interface Channels of Knowledge-Graph Tool Use

A study on the performance of a knowledge-graph tool use recipe with large language models.

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Peak-Then-Collapse and the Four Interface Channels of Knowledge-Graph Tool Use

By Tianda Sun, Dimitar KazakovarXiv
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The authors test a standard recipe for using knowledge graphs with large language models, observing a 'peak-then-collapse' pattern in performance. They identify four recurring failure modes and argue that interface feedback is a key difference from other tools.

The study also explores the effect of self-distillation as a mitigation strategy.

Abstract

The authors test a standard recipe for using knowledge graphs with large language models, observing a 'peak-then-collapse' pattern in performance. They identify four recurring failure modes and argue that interface feedback is a key difference from other tools. The study also explores the effect of self-distillation as a mitigation strategy.

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knowledge graph tool uselarge language modelspeak-then-collapse patterninterface feedbackself-distillationKnowledge GraphsLarge Language ModelsRetrieval & RAGSemantic Interoperability
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Peak-Then-Collapse and the Four Interface Channels of Knowledge-Graph Tool Use | Aramai