Coannotating: Uncertainty-guided work allocation between human and large language models for data annotation
Annotated data plays a critical role in Natural Language Processing (NLP) in training
models and evaluating their performance. Given recent developments in Large Language …
models and evaluating their performance. Given recent developments in Large Language …
A survey on contextualised semantic shift detection
S Montanelli, F Periti - arXiv preprint arXiv:2304.01666, 2023 - arxiv.org
Semantic Shift Detection (SSD) is the task of identifying, interpreting, and assessing the
possible change over time in the meanings of a target word. Traditionally, SSD has been …
possible change over time in the meanings of a target word. Traditionally, SSD has been …
Lexical Semantic Change through Large Language Models: a Survey
F Periti, S Montanelli - ACM Computing Surveys, 2024 - dl.acm.org
Lexical Semantic Change (LSC) is the task of identifying, interpreting, and assessing the
possible change over time in the meanings of a target word. Traditionally, LSC has been …
possible change over time in the meanings of a target word. Traditionally, LSC has been …
A systematic comparison of contextualized word embeddings for lexical semantic change
F Periti, N Tahmasebi - arXiv preprint arXiv:2402.12011, 2024 - arxiv.org
Contextualized embeddings are the preferred tool for modeling Lexical Semantic Change
(LSC). Current evaluations typically focus on a specific task known as Graded Change …
(LSC). Current evaluations typically focus on a specific task known as Graded Change …
(Chat) GPT v BERT: Dawn of Justice for Semantic Change Detection
In the universe of Natural Language Processing, Transformer-based language models like
BERT and (Chat) GPT have emerged as lexical superheroes with great power to solve open …
BERT and (Chat) GPT have emerged as lexical superheroes with great power to solve open …
Tweet insights: a visualization platform to extract temporal insights from twitter
This paper introduces a large collection of time series data derived from Twitter,
postprocessed using word embedding techniques, as well as specialized fine-tuned …
postprocessed using word embedding techniques, as well as specialized fine-tuned …
SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research
Despite its relevance, the maturity of NLP for social media pales in comparison with general-
purpose models, metrics and benchmarks. This fragmented landscape makes it hard for the …
purpose models, metrics and benchmarks. This fragmented landscape makes it hard for the …
The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks
Lexical Semantic Change Detection (LSCD) is a complex, lemma-level task, which is usually
operationalized based on two subsequently applied usage-level tasks: First, Word-in …
operationalized based on two subsequently applied usage-level tasks: First, Word-in …
[PDF][PDF] The Time-Embedding Travelers at WiC-ITA.
F Periti, H Dubossarsky - EVALITA, 2023 - ceur-ws.org
The WiC-ITA shared task aims to determine whether a word appearing in two distinct
sentences carries the same meaning. The task consists of two subtasks: binary classification …
sentences carries the same meaning. The task consists of two subtasks: binary classification …
[HTML][HTML] A Dataset for Evaluating Contextualized Representation of Biomedical Concepts in Language Models
Due to the complexity of the biomedical domain, the ability to capture semantically
meaningful representations of terms in context is a long-standing challenge. Despite …
meaningful representations of terms in context is a long-standing challenge. Despite …