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Dimosthenis Antypas

5 accepted papers

2025

Automatic Extraction of Metaphoric Analogies from Literary Texts: Task Formulation, Dataset Construction, and Evaluation

Joanne Boisson, Zara Siddique, Hsuvas Borkakoty, Dimosthenis Antypas, Luis Espinosa Anke, Jose Camacho-Collados
COLING 2025main

Extracting metaphors and analogies from free text requires high-level reasoning abilities such as abstraction and language understanding. Our study focuses on the extraction of the concepts forming metaphoric analogies in literary texts. To this end, we construct a novel dataset in this domain with…

Cited by 1Source ↗PDF ↗code ↗Scholar ↗
2024

BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

Junho Myung, Nayeon Lee, Yi Zhou, Jiho Jin, Rifki Afina Putri, Dimosthenis Antypas +16
NeurIPS 2024poster

Large language models (LLMs) often lack culture-specific everyday knowledge, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LLMs' cultural sensitivities are usually limited to a single language or online sources like Wikipedia, which may not reflect t…

Cited by 48Source ↗PDF ↗code ↗Scholar ↗
2024

Multilingual Topic Classification in X: Dataset and Analysis

Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, Jose Camacho-Collados
EMNLP 2024main

In the dynamic realm of social media, diverse topics are discussed daily, transcending linguistic boundaries. However, the complexities of understanding and categorising this content across various languages remain an important challenge with traditional techniques like topic modelling often struggl…

Cited by 0Source ↗PDF ↗Scholar ↗
2023

SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research

Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, Leonardo Neves, Kiamehr Rezaee, Luis Espinosa-Anke +2
EMNLP 2023long findings

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 community to know, for instance, given a task, which is the best performing model and how it compares with others. To a…

Cited by 0Source ↗Scholar ↗
2022

Twitter Topic Classification

Dimosthenis Antypas, Asahi Ushio, Jose Camacho-Collados, Vitor Silva, Leonardo Neves, Francesco Barbieri
COLING 2022main

Social media platforms host discussions about a wide variety of topics that arise everyday. Making sense of all the content and organising it into categories is an arduous task. A common way to deal with this issue is relying on topic modeling, but topics discovered using this technique are difficul…

Cited by 72Source ↗PDF ↗Scholar ↗