We present the results of HAHA at IberLEF 2021: Humor Analysis based on Human Annotation. This year's edition of the competition includes the two classic tasks of humor detection and rating, plus two ...novel tasks of humor logic mechanism and target classification. We describe the corpus created for the challenge, the competition phases, the submitted systems and the main results obtained.
We present the first shared task for detecting and analyzing codeswitching in Guarani and Spanish, GUA-SPA at IberLEF 2023. The challenge consisted of three tasks: identifying the language of a ...token, NER, and a novel task of classifying the way a Spanish span is used in the code-switched context. We annotated a corpus of 1500 texts extracted from news articles and tweets, around 25 thousand tokens, with the information for the tasks. Three teams took part in the evaluation phase, obtaining in general good results for Task 1, and more mixed results for Tasks 2 and 3.
We present the results of the QuALES task, which addresses the problem of Extractive Question Answering from texts. For both training and evaluation we use the QuALES corpus, a corpus of Uruguayan ...media news about the Covid-19 pandemic and related topics. We describe the systems developed by seven participants, all of them based on different BERT-like language models. The best results were obtained using the multilingual RoBERTa model pre-trained with SQUAD-Es-V2, with a fine tuning on the QuALES corpus.
In role-playing games a Game Master (GM) is the player in charge of the game, who must design the challenges the players face and narrate the outcomes of their actions. In this work we discuss some ...challenges to model GMs from an Interactive Storytelling and Natural Language Processing perspective. Following those challenges we propose three test categories to evaluate such dialogue systems, and we use them to test ChatGPT, Bard and OpenAssistant as out-of-the-box GMs.
We present the first shared task for detecting and analyzing code-switching in Guarani and Spanish, GUA-SPA at IberLEF 2023. The challenge consisted of three tasks: identifying the language of a ...token, NER, and a novel task of classifying the way a Spanish span is used in the code-switched context. We annotated a corpus of 1500 texts extracted from news articles and tweets, around 25 thousand tokens, with the information for the tasks. Three teams took part in the evaluation phase, obtaining in general good results for Task 1, and more mixed results for Tasks 2 and 3.
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual ...and textual data. However, most of the current VQA models use datasets that are primarily focused on English and a few major world languages, with images that are typically Western-centric. While recent efforts have tried to increase the number of languages covered on VQA datasets, they still lack diversity in low-resource languages. More importantly, although these datasets often extend their linguistic range via translation or some other approaches, they usually keep images the same, resulting in narrow cultural representation. To address these limitations, we construct CVQA, a new Culturally-diverse multilingual Visual Question Answering benchmark, designed to cover a rich set of languages and cultures, where we engage native speakers and cultural experts in the data collection process. As a result, CVQA includes culturally-driven images and questions from across 28 countries on four continents, covering 26 languages with 11 scripts, providing a total of 9k questions. We then benchmark several Multimodal Large Language Models (MLLMs) on CVQA, and show that the dataset is challenging for the current state-of-the-art models. This benchmark can serve as a probing evaluation suite for assessing the cultural capability and bias of multimodal models and hopefully encourage more research efforts toward increasing cultural awareness and linguistic diversity in this field.
The coffee berry borer (CBB);
Hypothenemus hampei
(Coleoptera: Curculionidae), is widely recognized as the major insect pest of coffee crops. Like many other arthropods, CBB harbors numerous bacteria ...species that may have important physiological roles in host nutrition, detoxification, immunity and protection. To date, the structure and dynamics of the gut-associated bacterial community across the CBB life cycle is not yet well understood. A better understanding of the complex relationship between CBB and its bacterial companions may provide new opportunities for insect control. In the current investigation, we analyzed the diversity and abundance of gut microbiota across the CBB developmental stages under field conditions by using high-throughput Illumina sequencing of the 16S ribosomal RNA gene. Overall, 15 bacterial phyla, 38 classes, 61 orders, 101 families and 177 genera were identified across all life stages, including egg, larva 1, larva 2, pupa, and adults (female and male). Proteobacteria and Firmicutes phyla dominated the microbiota along the entire insect life cycle. Among the 177 genera, the 10 most abundant were members of
Ochrobactrum
(15.1%),
Pantoea
(6.6%),
Erwinia
(5.7%),
Lactobacillus
(4.3%),
Acinetobacter
(3.4%),
Stenotrophomonas
(3.1%),
Akkermansia
(3.0%),
Agrobacterium
(2.9%),
Curtobacterium
(2.7%), and
Clostridium
(2.7%). We found that the overall bacterial composition is diverse, variable within each life stage and appears to vary across development. About 20% of the identified OTUs were shared across all life stages, from which 28 OTUs were consistently found in all life stage replicates. Among these OTUs there are members of genera
Pantoea
,
Erwinia
,
Agrobacterium
,
Ochrobactrum
,
Pseudomonas
,
Acinetobacter
,
Brachybacterium
,
Sphingomonas
and
Methylobacterium
, which can be considered as the gut-associated core microbiota of
H. hampei
. Our findings bring additional data to enrich the understanding of gut microbiota in CBB and its possible use for development of insect control strategies.
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