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Found 14 papers, 3 papers with code
Centroid-based Text Summarization through Compositionality of Word Embeddings
The textual similarity is a crucial aspect for many extractive text summarization methods.
DUKweb: Diachronic word representations from the UK Web Archive corpus
Lexical semantic change (detecting shifts in the meaning and usage of words) is an important task for social and cultural studies as well as for Natural Language Processing applications.
Iterative Multi-document Neural Attention for Multiple Answer Prediction
People have information needs of varying complexity, which can be solved by an intelligent agent able to answer questions formulated in a proper way, eventually considering user context and preferences.
Diachronic Analysis of Entities by Exploiting Wikipedia Page revisions
In the last few years, the increasing availability of large corpora spanning several time periods has opened new opportunities for the diachronic analysis of language.
Mining the UK Web Archive for Semantic Change Detection
Semantic change detection (i. e., identifying words whose meaning has changed over time) started emerging as a growing area of research over the past decade, with important downstream applications in natural language processing, historical linguistics and computational social science.
GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering
This paper describes the system proposed for the SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection.
The Corpora They Are a-Changing: a Case Study in Italian Newspapers
The use of automatic methods for the study of lexical semantic change (LSC) has led to the creation of evaluation benchmarks.
LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language
By leveraging an open science philosophy, this study contributes to Language Adaptation strategies for the Italian language by introducing the novel LLaMAntino family of Italian LLMs.
