Search Results for author: Santiago Castro

Found 15 papers, 11 papers with code

In-the-Wild Video Question Answering

no code implementations COLING 2022 Santiago Castro, Naihao Deng, Pingxuan Huang, Mihai Burzo, Rada Mihalcea

Existing video understanding datasets mostly focus on human interactions, with little attention being paid to the “in the wild” settings, where the videos are recorded outdoors.

Evidence Selection Question Answering +2

WildQA: In-the-Wild Video Question Answering

no code implementations14 Sep 2022 Santiago Castro, Naihao Deng, Pingxuan Huang, Mihai Burzo, Rada Mihalcea

Existing video understanding datasets mostly focus on human interactions, with little attention being paid to the "in the wild" settings, where the videos are recorded outdoors.

Evidence Selection Question Answering +2

FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks

1 code implementation24 Mar 2022 Santiago Castro, Fabian Caba Heilbron

Large-scale pretrained image-text models have shown incredible zero-shot performance in a handful of tasks, including video ones such as action recognition and text-to-video retrieval.

Action Recognition Retrieval +4

FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation Framework

1 code implementation ACL 2022 Santiago Castro, Ruoyao Wang, Pingxuan Huang, Ian Stewart, Oana Ignat, Nan Liu, Jonathan C. Stroud, Rada Mihalcea

We propose fill-in-the-blanks as a video understanding evaluation framework and introduce FIBER -- a novel dataset consisting of 28, 000 videos and descriptions in support of this evaluation framework.

Language Modelling Multiple-choice +4

HAHA 2019 Dataset: A Corpus for Humor Analysis in Spanish

no code implementations LREC 2020 Luis Chiruzzo, Santiago Castro, Aiala Ros{\'a}

This paper presents the development of a corpus of 30, 000 Spanish tweets that were crowd-annotated with humor value and funniness score.

Towards Multimodal Sarcasm Detection (An \_Obviously\_ Perfect Paper)

1 code implementation ACL 2019 Santiago Castro, Devamanyu Hazarika, Ver{\'o}nica P{\'e}rez-Rosas, Roger Zimmermann, Rada Mihalcea, Soujanya Poria

As a first step towards enabling the development of multimodal approaches for sarcasm detection, we propose a new sarcasm dataset, Multimodal Sarcasm Detection Dataset (MUStARD), compiled from popular TV shows.

Sarcasm Detection

Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

1 code implementation5 Jun 2019 Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, Roger Zimmermann, Rada Mihalcea, Soujanya Poria

As a first step towards enabling the development of multimodal approaches for sarcasm detection, we propose a new sarcasm dataset, Multimodal Sarcasm Detection Dataset (MUStARD), compiled from popular TV shows.

Sarcasm Detection

A High Coverage Method for Automatic False Friends Detection for Spanish and Portuguese

1 code implementation COLING 2018 Santiago Castro, Jairo Bonanata, Aiala Ros{\'a}

In this work we propose a high coverage method that uses word vector representations to build a false friends classifier for any pair of languages, which we apply to the particular case of Spanish and Portuguese.

RETUYT in TASS 2017: Sentiment Analysis for Spanish Tweets using SVM and CNN

no code implementations17 Oct 2017 Aiala Rosá, Luis Chiruzzo, Mathias Etcheverry, Santiago Castro

This article presents classifiers based on SVM and Convolutional Neural Networks (CNN) for the TASS 2017 challenge on tweets sentiment analysis.

Sentiment Analysis Word Embeddings

A Crowd-Annotated Spanish Corpus for Humor Analysis

1 code implementation WS 2018 Santiago Castro, Luis Chiruzzo, Aiala Rosá, Diego Garat, Guillermo Moncecchi

Computational Humor involves several tasks, such as humor recognition, humor generation, and humor scoring, for which it is useful to have human-curated data.

Humor Detection

Is This a Joke? Detecting Humor in Spanish Tweets

1 code implementation28 Mar 2017 Santiago Castro, Matías Cubero, Diego Garat, Guillermo Moncecchi

While humor has been historically studied from a psychological, cognitive and linguistic standpoint, its study from a computational perspective is an area yet to be explored in Computational Linguistics.

Humor Detection

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