Please commit a related paper for a good survey and discuss (I don't have a plan to publish a survey paper).
- From Word to Sense Embeddings: A Survey on Vector Representations of Meaning, 2018.
- Word Embeddings: A Survey, 2019.
- Retrofitting Word Vectors to Semantic Lexicons, 2015.
- De-Conflated Semantic Representations, 2016.
- GenSense: A Generalized Sense Retrofitting Model, 2018.
- SENSEMBED: Learning Sense Embeddings for Word and Relational Similarity, 2015.
- Multi-sense embeddings through a word sense disambiguation process Author links open overlay panel, 2019.
- SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation, 2020.
- Multi-prototype vector-space models of word meaning, 2010.
- Improving Word Representations via Global Contextand Multiple Word Prototypes, 2012.
- K-Embeddings: Learning Conceptual Embeddings for Words using Context, 2016.
- Multimodal Word Distributions, 2017.
- Which Evaluations Uncover Sense Representations that Actually Make Sense?, 2020. ※ This paper also proposes the threshold for pruning that can calculate. However, it can use all methods because this is not belonging to Non-Parametric.
- A Mixture Model for Learning Multi-Sense Word Embeddings, 2017.
- Learning Topic-Sensitive Word Representations, 2017.
- Jointly Learning Word Embeddings and Latent Topics, 2017.
- Decoupled Word Embeddings using Latent Topics, 2020.
- Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space, 2014.
- CODE original github and reimplement?
- Multi Sense Embeddings from Topic Models, 2019.
- sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings, 2015.
- NASARI: a Novel Approach to a Semantically-Aware Representation of Items, 2015.
- Word2Sense: Sparse Interpretable Word Embeddings, 2020.
- Conception: Multilingually-Enhanced, Human-Readable Concept Vector Representations, 2020.
For Japanese, 言語処理における分散表現学習のフロンティア, 2016.
ACL page https://aclweb.org/aclwiki/Analogy_(State_of_the_art).
ACL page https://aclweb.org/aclwiki/Similarity_(State_of_the_art).
- SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity
- MSD-1030: A Well-built Multi-Sense Evaluation Dataset for Sense Representation Models, 2020.
- SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation, 2015.
- Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity, 2020.
- SCWS Improving Word Representations via Global Contextand Multiple Word Prototypes, 2012. # dupliates
- SemEval-2020 Task 3: Graded Word Similarity in Context, 2020.
- WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations, 2019.
- XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization, 2020.
- SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC), 2021.
- WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context, 2021.
- github memory survey https://githubmemory.com/repo/aflyhat/awesome-sentence-embedding, -2019.
- Word Representation, 2020.
- A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models, 2021.
- Efficient Estimation of Word Representations in Vector Space, 2013.
- Distributed Representations of Words and Phrases and their Compositionality, 2013.
- GloVe: Global Vectors for Word Representation, 2014.
- Word Representations via Gaussian Embedding, 2014.
- Poincaré Embeddings for Learning Hierarchical Representations, 2017.
- Enriching Word Vectors with Subword Information, 2017.
- Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings, 2020.
survey page https://github.com/tomohideshibata/BERT-related-papers.
- Deep Contextualized Word Representations, 2018.
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, 2019.
- Towards Qualitative Word Embeddings Evaluation: Measuring Neighbors Variation, 2018.
- Deconstructing word embedding algorithms, 2020.
- Unsupervised Word Polysemy Quantification with Multiresolution Grids of Contextual Embeddings, 2020.
- Are All Good Word Vector Spaces Isomorphic?, 2020.
- 単語埋め込みによる論理演算, 2021.
- A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space, 2021.
- Monitoring geometrical properties of word embeddings for detecting the emergence of new topics, 2021.
- Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation, 2019.
- With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation, 2020.