Papers with language model-based methods

1 papers
Inductive Reasoning on Few-Shot Knowledge Graphs with Task-Aware Language Models (2025.findings-emnlp)

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Challenge: Current knowledge graph reasoning methods rely on extensive structural information to perform in these few-shot scenarios.
Approach: They propose a task-aware language model that activates the language model’s in-context learning ability for structured KG tasks.
Outcome: The proposed method achieves state-of-the-art in few-shot scenarios while reducing the inference time required by previous methods.

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