Papers with zero-shot recognition

2 papers
NERetrieve: Dataset for Next Generation Named Entity Recognition and Retrieval (2023.findings-emnlp)

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Challenge: Named Entity Recognition (NER) is a widely adopted NLP task . authors present three variants of NER task, with dataset to support them .
Approach: They propose three variants of the NER task, together with a dataset to support them . they propose a move towards more fine-grained entities and zero-shot recognition .
Outcome: The proposed model matches or surpasses existing models in NER tasks . the proposed model is based on a large, silver-annotated corpus of 4 million paragraphs .
iKnow-audio: Integrating Knowledge Graphs with Audio-Language Models (2025.emnlp-main)

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Challenge: Contrastive language-audio pretraining models learn by aligning audio and text in a shared embedding space.
Approach: They propose a framework that integrates knowledge graphs with audio-language models to provide robust semantic grounding.
Outcome: iKnow-audio improves disambiguation of acoustically similar sounds and reduces prompt engineering.

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