@inproceedings{godbole-etal-2022-temporal,
    title = "Temporal Word Meaning Disambiguation using {T}ime{LM}s",
    author = "Godbole, Mihir  and
      Dandavate, Parth  and
      Kane, Aditya",
    editor = "Barbieri, Francesco  and
      Camacho-Collados, Jose  and
      Dhingra, Bhuwan  and
      Espinosa-Anke, Luis  and
      Gribovskaya, Elena  and
      Lazaridou, Angeliki  and
      Loureiro, Daniel  and
      Neves, Leonardo",
    booktitle = "Proceedings of the First Workshop on Ever Evolving NLP (EvoNLP)",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2022.evonlp-1.8/",
    doi = "10.18653/v1/2022.evonlp-1.8",
    pages = "55--60",
    abstract = "Meaning of words constantly change given the events in modern civilization. Large Language Models use word embeddings, which are often static and thus cannot cope with this semantic change. Thus, it is important to resolve ambiguity in word meanings. This paper is an effort in this direction, where we explore methods for word sense disambiguation for the EvoNLP shared task. We conduct rigorous ablations for two solutions to this problem. We see that an approach using time-aware language models helps this task. Furthermore, we explore possible future directions to this problem."
}