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Found 12 papers, 1 papers with code
中文专利关键信息语料库的构建研究(Research on the construction of Chinese patent key information corpus)
“专利文献是一种重要的技术文献, 是知识产权强国的重要工作内容。目前专利语料库多集中于信息检索、机器翻译以及文本文分类等领域, 尚缺乏更细粒度的标注, 不足以支持问答、阅读理解等新形态的人工智能技术研发。本文面向专利智能分析的需要, 提出了从解决问题、技术手段、效果三个角度对发明专利进行专利标注, 并最终构建了包含313篇的中文专利关键信息语料库。利用命名实体识别技术对语料库关键信息进行识别和验证, 表明专利关键信息的识别是不同于领域命名实体识别的更大粒度的信息抽取难题。”
Self-Evaluation of Large Language Model based on Glass-box Features
The proliferation of open-source Large Language Models (LLMs) underscores the pressing need for evaluation methods.
An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Models are Task-specific Classifiers
Recently, there has been a growing trend of utilizing Large Language Model (LLM) to evaluate the quality of other LLMs.
Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models
We conduct extensive experiments on various Chinese NLP tasks to evaluate existing PLMs as well as the proposed MigBERT.
Robust Machine Reading Comprehension by Learning Soft labels
Neural models have achieved great success on the task of machine reading comprehension (MRC), which are typically trained on hard labels.
End-to-End Speech Translation with Adversarial Training
End-to-End speech translation usually leverages audio-to-text parallel data to train an available speech translation model which has shown impressive results on various speech translation tasks.
Investigating the content and form of referring expressions in Mandarin: introducing the Mtuna corpus
East Asian languages are thought to handle reference differently from languages such as English, particularly in terms of the marking of definiteness and number.
