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Found 4 papers, 3 papers with code
MProto: Multi-Prototype Network with Denoised Optimal Transport for Distantly Supervised Named Entity Recognition
Distantly supervised named entity recognition (DS-NER) aims to locate entity mentions and classify their types with only knowledge bases or gazetteers and unlabeled corpus.
PUMGPT: A Large Vision-Language Model for Product Understanding
Simultaneously, we utilize open-domain datasets during training to improve the performance of PUMGPT and its generalization ability.
PromptNER: Prompt Locating and Typing for Named Entity Recognition
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks.
Ranked #1 on
Nested Named Entity Recognition
on ACE 2004
Propose-and-Refine: A Two-Stage Set Prediction Network for Nested Named Entity Recognition
In the refine stage, proposals interact with each other, and richer contextual information is incorporated into the proposal representations.
