Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison.
Alessandro Raganato, Jose Camacho-Collados, Roberto Navigli.
(EACL 2017)
[paper]

Neural Sequence Learning Models for Word Sense Disambiguation.
Alessandro Raganato, Claudio Delli Bovi, Roberto Navigli.
(EMNLP 2017)
[paper]

Incorporating Glosses into Neural Word Sense Disambiguation.
Fuli Luo, Tianyu Liu, Qiaolin Xia, Baobao Chang, Zhifang Sui.
(ACL 2018)
[paper] [code]

Leveraging Gloss Knowledge in Neural Word Sense Disambiguation by Hierarchical Co-Attention.
Fuli Luo, Tianyu Liu, Zexue He, Qiaolin Xia, Zhifang Sui, Baobao Chang.
(EMNLP 2018)
[paper]

WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations.
Mohammad Taher Pilehvar, Jose Camacho-Collados.
(NAACL 2019)
[paper] [project site]

Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings.
Gregor Wiedemann, Steffen Remus, Avi Chawla, Chris Biemann.
(Conference on Natural Language Processing (KONVENS) 2019)
[paper] [code]

Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation.
Daniel Loureiro, Alípio Mário Jorge.
(ACL 2019)
[paper] [code]

Zero-shot Word Sense Disambiguation using Sense Definition Embeddings.
Sawan Kumar, Sharmistha Jat, Karan Saxena, Partha Talukdar.
(ACL 2019)
[paper] [code]

Just “OneSeC” for Producing Multilingual Sense-Annotated Data.
Bianca Scarlini, Tommaso Pasini, Roberto Navigli.
(ACL 2019)
[paper]

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge.
Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang.
(EMNLP 2019)
[paper]

Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations.
Christian Hadiwinoto, Hwee Tou Ng, Wee Chung Gan.
(EMNLP 2019)
[paper]

SyntagNet: Challenging Supervised Word Sense Disambiguation with Lexical-Semantic Combinations.
Marco Maru, Federico Scozzafava, Federico Martelli, Roberto Navigli.
(EMNLP 2019)
[paper]

Game Theory Meets Embeddings: a Unified Framework for Word Sense Disambiguation.
Rocco Tripodi, Roberto Navigli.
(EMNLP 2019)
[paper]

Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation.
Loïc Vial, Benjamin Lecouteux, Didier Schwab.
(Global Wordnet Conference (GWC) 2019)
[paper]

SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation.
Bianca Scarlini, Tommaso Pasini, Roberto Navigli.
(AAAI 2020)
[paper] [project site]

CSI: A Coarse Sense Inventory for 85% Word Sense Disambiguation.
Caterina Lacerra, Michele Bevilacqua, Tommaso Pasini, Roberto Navigli.
(AAAI 2020)
[paper] [project site]

Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information.
Michele Bevilacqua, Roberto Navigli.
(ACL 2020)
[paper]

Moving Down the Long Tail of Word Sense Disambiguationwith Gloss Informed Bi-encoders.
Terra Blevins, Luke Zettlemoyer.
(ACL 2020)
[paper] [code]

Don't Neglect the Obvious: On the Role of Unambiguous Words in Word Sense Disambiguation.
Daniel Loureiro, Jose Camacho-Collados.
(EMNLP 2020)
[paper] [data&code]

With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation.
Bianca Scarlini, Tommaso Pasini, Roberto Navigli.
(EMNLP 2020)
[paper] [website]

Language Models and Word Sense Disambiguation: An Overview and Analysis.
Daniel Loureiro, Kiamehr Rezaee, Mohammad Taher Pilehvar, Jose Camacho-Collados.
(Computational Linguistics 2021)
[paper]

FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary.
Terra Blevins, Mandar Joshi, Luke Zettlemoyer.
(EACL 2021)
[paper] [website] [code]

Non-Parametric Few-Shot Learning for Word Sense Disambiguation.
Howard Chen, Mengzhou Xia, Danqi Chen.
(NAACL 2021)
[paper] [code]