80 citations · 80 across the 4 of their papers we have counts for
4 papers
E2E-GMNER: End-to-End Generative Grounded Multimodal Named Entity Recognition
Meng Zhang, Jinzhong Ning, Xiaolong Wu +2
Grounded Multimodal Named Entity Recognition (GMNER) aims to jointly identify named entity mentions in text, predict their semantic types, and ground each entity to a corresponding…
A Multi-Agent LLM Framework for Multi-Domain Low-Resource In-Context NER via Knowledge Retrieval, Disambiguation and Reflective Analysis
Wenxuan Mu, Jinzhong Ning, Di Zhao +1
In-context learning (ICL) with large language models (LLMs) has emerged as a promising paradigm for named entity recognition (NER) in low-resource scenarios. However, existing ICL-…
CommonVoice-SpeechRE and RPG-MoGe: Advancing Speech Relation Extraction with a New Dataset and Multi-Order Generative Framework
Jinzhong Ning, Paerhati Tulajiang, Yingying Le +4
Speech Relation Extraction (SpeechRE) aims to extract relation triplets directly from speech. However, existing benchmark datasets rely heavily on synthetic data, lacking sufficien…
Taiyi: A Bilingual Fine-Tuned Large Language Model for Diverse Biomedical Tasks
Ling Luo, Jinzhong Ning, Yingwen Zhao +17
Objective: Most existing fine-tuned biomedical large language models (LLMs) focus on enhancing performance in monolingual biomedical question answering and conversation tasks. To i…