Washington Cunha
Orcid: 0000-0002-1988-8412
According to our database1,
Washington Cunha
authored at least 28 papers
between 2020 and 2025.
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Bibliography
2025
CoRR, July, 2025
CTDGSI: A comprehensive exploitation of instance selection methods for automatic text classification. VII Concurso de Teses, Dissertações e Trabalhos de Graduação em SI - XXI Simpósio Brasileiro de Sistemas de Informação.
CoRR, June, 2025
A thorough benchmark of automatic text classification: From traditional approaches to large language models.
CoRR, April, 2025
ACM Trans. Inf. Syst., March, 2025
Why are you traveling? Inferring trip profiles from online reviews and domain-knowledge.
Online Soc. Networks Media, 2025
Characterizing YouTube's Role in Online Gambling Promotion: A Case Study of Fortune Tiger in Brazil.
Proceedings of the 17th ACM Web Science Conference 2025, 2025
Optimizing Tail-Head Trade-off for Extreme Multi-Label Text Classification (XMTC) with RAG-Labels and a Dynamic Two-Stage Retrieval and Fusion Pipeline.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
Proceedings of the Advances in Information Retrieval, 2025
Instance-Selection-Inspired Undersampling Strategies for Bias Reduction in Small and Large Language Models for Binary Text Classification.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
Pipelining Semantic Expansion and Noise Filtering for Sentiment Analysis of Short Documents - CluSent Method.
J. Interact. Syst., 2024
On Representation Learning-based Methods for Effective, Efficient, and Scalable Code Retrieval.
Neurocomputing, 2024
A Strategy to Combine 1stGen Transformers and Open LLMs for Automatic Text Classification.
CoRR, 2024
PATopics: An automatic framework to extract useful information from pharmaceutical patents documents.
CoRR, 2024
Is it a work or leisure travel? Applying text classification to identify work-related travel on social networks.
CoRR, 2024
A Novel Two-Step Fine-Tuning Pipeline for Cold-Start Active Learning in Text Classification Tasks.
CoRR, 2024
Proceedings of the 14th Italian Information Retrieval Workshop, 2024
A Quantum Annealing Instance Selection Approach for Efficient and Effective Transformer Fine-Tuning.
Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval, 2024
2023
On the class separability of contextual embeddings representations - or "The classifier does not matter when the (text) representation is so good!".
Inf. Process. Manag., 2023
A Comparative Survey of Instance Selection Methods applied to Non-Neural and Transformer-Based Text Classification.
ACM Comput. Surv., 2023
TPDR: A Novel Two-Step Transformer-based Product and Class Description Match and Retrieval Method.
CoRR, 2023
CluSent - Combining Semantic Expansion and De-Noising for Dataset-Oriented Sentiment Analysis of Short Texts.
Proceedings of the 29th Brazilian Symposium on Multimedia and the Web, 2023
An Effective, Efficient, and Scalable Confidence-based Instance Selection Framework for Transformer-Based Text Classification.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Uma Metodologia para Tratamento do Viés da Maioria em Modelos de Stacking via Identificação de Documentos Difíceis.
Proceedings of the 38th Brazilian Symposium on Databases, 2023
2022
Proceedings of the WebMedia '22: Brazilian Symposium on Multimedia and Web, Curitiba, Brazil, November 7, 2022
2021
On the cost-effectiveness of neural and non-neural approaches and representations for text classification: A comprehensive comparative study.
Inf. Process. Manag., 2021
2020
Extended pre-processing pipeline for text classification: On the role of meta-feature representations, sparsification and selective sampling.
Inf. Process. Manag., 2020
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020