首先是Internal Representations Tenney et al probe了编码在上下文表示里的语言学知识。主要的工作包括: 在一些辅助任务上(Part-of-Speech, Constituents, Dependencies, Entities, Semantic Role Labelling, Semantic Proto Roles, and Coreference resolutions)比较了一些基于上下文表示的模型(BERT, GPT, ELMO, and CoVe...
「ICLR,全称为「International Conference on Learning Representations」(国际学习表征会议)」,2013 年5月2日至5月4日在美国亚利桑那州斯科茨代尔顺利举办了第一届ICLR会议。「该会议是一年一度的会议(会议等级A类)」,截止到2022年它已经举办了10届,而今年的(2023年)5月1日至5日,将在基加利卢旺达举办ICLR的第十一...
unsupervised parsing, ...) online开会的时候相较于其他track, syntax track根本没人来 相当惨了可以说...
Hewitt 和 Manning 在论文 A Structural Probe for Finding Syntax in Word Representations 中提出了 “结构性探针” 的概念,从经验上来说,将内部表示的空间转换为语言知识的空间是可能实现的。探针识别一种线性变换,在这个变换下,变换表示的 L2 平方距离编码解析树中单词之间的距离,而变换表示的 L2 平方范数编码解...
methods includeword embeddingslike Word2Vec or GloVe, which represent words as dense vectors in a continuous space, capturing semantic relationships between words. Contextual embeddings further enhance this by considering the context in which words appear, allowing for richer, more nuanced representations...
Symbolic, Distributed and Distributional Representations for Natural Language Processing in the Era of Deep Learning: a Survey.Frontiers Robotics AI 2017paperbib Lorenzo Ferrone, Fabio Massimo Zanzotto Syntax Representation in Word Embeddings and Neural Networks -- A Survey.ITAT 2020paperbib ...
Representations have been shown to be predictive of certain linguistic phenomena such as alignments in translation or syntactic hierarchies. Better performance has been achieved when pretraining with syntax; even when syntax is not explicitly encoded, representations still learn some notion of syntax ( ...
📙 Recent Advances in NLP via Large Pre-Trained Language Models: A Survey [Paper, November 2021] Embeddings Repositories ⭐ Pre-trained ELMo Representations for Many Languages [GitHub, 1458 stars] ⭐ sense2vec - Contextually-keyed word vectors [GitHub, 1617 stars] ⭐ wikipedia2vec [GitHub...
Phonology(语音学)、morphology(词法)和 syntax(句法) Return of empiricism(经验主义的回归) IBM 为语音识别开发的概率模型 在part-of-speech tagging(词性标注)、parsing(解析)和 semantics(语义)方面启发了其他的数据驱动方法 基于held-out data(保留数据)、quantitative metrics(定量指标),以及和最新技术进行比较的...
一、Deep contextualized word representations 作者：Matthew E. Peters / Mark Neumann / Mohit Iyyer ...