Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Cabello Laura"'
Question answering is a natural language understanding task that involves reasoning over both explicit context and unstated, relevant domain knowledge. Large language models (LLMs), which underpin most contemporary question answering systems, struggl
Externí odkaz:
http://arxiv.org/abs/2411.03883
Autor:
Cabello, Laura, Akujuobi, Uchenna
Aspect-Based Sentiment Analysis (ABSA) involves extracting opinions from textual data about specific entities and their corresponding aspects through various complementary subtasks. Several prior research has focused on developing ad hoc designs of v
Externí odkaz:
http://arxiv.org/abs/2405.20703
Pretrained machine learning models are known to perpetuate and even amplify existing biases in data, which can result in unfair outcomes that ultimately impact user experience. Therefore, it is crucial to understand the mechanisms behind those prejud
Externí odkaz:
http://arxiv.org/abs/2310.17530
Contrastive explanations, where one decision is explained in contrast to another, are supposed to be closer to how humans explain a decision than non-contrastive explanations, where the decision is not necessarily referenced to an alternative. This c
Externí odkaz:
http://arxiv.org/abs/2310.11906
The recently released ChatGPT model demonstrates unprecedented capabilities in zero-shot question-answering. In this work, we probe ChatGPT for its conversational understanding and introduce a conversational framework (protocol) that can be adopted i
Externí odkaz:
http://arxiv.org/abs/2306.03024
Explainability methods are used to benchmark the extent to which model predictions align with human rationales i.e., are 'right for the right reasons'. Previous work has failed to acknowledge, however, that what counts as a rationale is sometimes sub
Externí odkaz:
http://arxiv.org/abs/2306.00639
The societal impact of pre-trained language models has prompted researchers to probe them for strong associations between protected attributes and value-loaded terms, from slur to prestigious job titles. Such work is said to probe models for bias or
Externí odkaz:
http://arxiv.org/abs/2304.10153
Detecting offensive language is a challenging task. Generalizing across different cultures and languages becomes even more challenging: besides lexical, syntactic and semantic differences, pragmatic aspects such as cultural norms and sensitivities, w
Externí odkaz:
http://arxiv.org/abs/2303.17927
The recent release of ChatGPT has garnered widespread recognition for its exceptional ability to generate human-like responses in dialogue. Given its usage by users from various nations and its training on a vast multilingual corpus that incorporates
Externí odkaz:
http://arxiv.org/abs/2303.17466
Autor:
Hernández, Judith, Pisón, Raquel Pinillos, Arnaiz, Eneritz Velasco, Villaverde, Serena, Vila, Sara, Rojo, Pablo, Epalza, Cristina, Moraleda, Cinta, Cooke, Elisa Fernández, Prieto, Luis, Zamora, Berta, Martínez de Aragón, Ana, Simón, Rogelio, Camacho, Ana, Machín, Fátima, Cabello, Laura, Romero, María Luz, Serna, Miquel, Martín, Marta, Esquivel-De la Fuente, Estrella, Calle, María de la, Rodríguez, Sara Domínguez, Cabanes, María, Gómez-Montes, Enery, Goncé, Anna, Bango, Marta Valdés, a<%2Fce%3Asup>+Carmen%22">Viñuela-Benéitez, M