(sorry about the bad joke, but we're also presenting a pun paper today at #EMNLP2025 and cannot stop thinking of puns! 😅)

Where would you like to see chess going over the next 10 years? Elite tournaments (mostly invitationals or more qualification-based?), rating (Elo or more tennis-style rankings encouraging participation?), variants (blitz/rapid, Freestyle), world championship cycle, etc. No need to cover everything!

You can find all the collections mentioned above in the Cardiff NLP Hugging Face page: huggingface.co/cardiffnlp

That’s all! Hope these resources can be helpful. Also, we welcome feedback and please let us know if you would like to find some additional models currently not supported! 🙏

Hate speech detection. Unfortunately, hateful content is widespread across the web, and it’s hard to detect it without automatic tools. We have developed general-purpose models for hate speech detection, including to classify according to the target community.

Topic classification. With a topic taxonomy tailored for social media, we release datasets and multilingual models for topic classification. With these models, you can filter or analyse content related to specific topics such as sports, science, news, music and 15 others.

Sentiment analysis. Since sentiment analysis is one of the most popular tasks when it comes to social media, we’ve created a separate collection with some of our popular sentiment-related resources, including multilingual models and a unified benchmark for 8 languages 🌍

Sensitive content. In social media we can find sensitive content such as hate speech, conflictual language, drug and sexual-related content, profanity, self-harm or spam. We release a dataset with these categories and models so you can customise your sensitive filters.

SuperTweetEval. This collection contains a benchmark with challenging datasets for NLP tasks in social media such as question answering, topic-based sentiment analysis, emoji prediction or tweet similarity. In addition to the datasets, we release custom models for each task.

TweetNLP. This is definitely our most popular collection 🔥 With millions of downloads every month and over 500 million downloads overall, this collection contains specialised NLP models for sentiment analysis, emotion detection, offensive language identification and more.

@camachocollados.bsky.social, Cardiff University
Title - "Multilinguality and Cultural Awareness in Language Models"