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近十年来澳门的词汇增长(Macau’s Vocabulary Growth in the Recent Ten Year)
“词汇增长模型可以通过拟合词种(types)与词例(tokens)之间的数量关系, 反映某一领域词汇的历时演化。澳门作为多语言多文化融合之地, 词汇的使用情况能够反映社会的关注焦点, 但目前尚无对澳门历时词汇演变的研究。本文首次构建澳门汉语历时语料库, 利用三大词汇增长模型拟合语料库的词汇变化, 并选取效果最好的 Heaps 模型进一步分析词汇演变与报刊内容的关系, 结果反映出澳门词汇的变化趋势与热点新闻、澳门施政方针和民生密切相关。本研究还采用去除文本时序信息后的乱序文本, 验证了方法的有效性。本文是首项基于大规模历时语料库考察澳门词汇演变的研究, 对深入了解澳门语言生活的发展具有重要意义。”
Towards Robustness of Text-to-Visualization Translation against Lexical and Phrasal Variability
Text-to-Vis is an emerging task in the natural language processing (NLP) area that aims to automatically generate data visualizations from natural language questions (NLQs).
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection
While large language models (LLMs) such as ChatGPT and PaLM have demonstrated remarkable performance in various language understanding and generation tasks, their capabilities in complex reasoning and intricate knowledge utilization still fall short of human-level proficiency.
MMLN: Leveraging Domain Knowledge for Multimodal Diagnosis
Recent studies show that deep learning models achieve good performance on medical imaging tasks such as diagnosis prediction.
Faster and Safer Training by Embedding High-Level Knowledge into Deep Reinforcement Learning
Deep reinforcement learning has been successfully used in many dynamic decision making domains, especially those with very large state spaces.
