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The proposed sequence labeling scheme enables the use of a shared architecture that learns the syntactic structures from both grammatical structures simultaneously and hence improves generalization.
Science, technology, and innovation policies are crucial for competitiveness, yet their diversity and scale make them difficult to map and monitor consistently. Existing approaches rely heavily on manual survey efforts, which are costly and challenging to scale across countries. Large language models (LLMs) enable new...
This paper uses several fine-tuned vision-language models as independent annotators and combines their span predictions through character-level majority voting, and additionally explores activation probes to indicate that disagreement among diverse models tracks disagreement among human annotators.
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