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Subsequently, the entire model undergoes fine-tuning to ensure improved adaptability to the expanded vocabulary and effective extraction of document layout features. By harnessing the exceptional language comprehension capabilities of LLMs, our model is capable of executing comprehensive entity extraction for...
Information Extraction (IE) aims to extract structural knowledge from plain natural language texts. Recently, generative Large Language Models (LLMs) have
近期对大型语言模型(LLMs,例如GPT-3、ChatGPT)的研究表明,这些模型在零样本设置下展现出了令人鼓舞的性能,从而激发了研究者探索基于提示的方法。本研究探讨了是否能够通过直接提示LLMs来构建强大的IE模型。具体来说,研究者将零样本IE任务转化为一个多轮问答问题,并提出了一个两阶段框架(ChatIE)。借助ChatGPT的力量,...
LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition Arxiv 2024-02 Structured information extraction from scientific text with large language models Nature Communications 2024-02 GitHub NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data Arxiv 202...
Through prompt engineering, combined with a few-shot learning strategy and a self-judgment mechanism, this method achieves automatic extraction of accident-cause entities and their relationships. Experimental results indicate that this approach effectively improves the accuracy of information extraction, ...
We find that all three of our LLM-NERRE host-dopant extraction models perform significantly better than either the MatBERT-Proximity or seq2rel baseline models. Of the two baselines, the seq2rel model achieves higher precision (0.420) and recall (0.605) resulting inF1 = 0.496, which is...
Therefore, it is necessary to explore how to build a unified information extraction (UIE) model with LLMs. Figure 1: Illustration of 3 different paradigms for solving unified information extraction task. Recently, Lu et al. (2022) proposed UIE, which uniformly encodes different extraction ...
它利用大型语言模型（LLMs）的能力来改进传统的IR系统。这种方法通过LLM代理自主地进行多步骤操作以达到...
In the past, the PLM (Pre-trained Language Model) model was mainly used for information extraction, but due to the complexity of the sequence semantic structure and task diversity, it is difficult for traditional PLM to achieve the desired effect. With the advancement of LLM (Large Language ...