Papers by Murilo Missano Bell
Analysis of Automated Document Relevance Annotation for Information Retrieval in Oil and Gas Industry (2025.emnlp-industry)
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João Vitor Mariano Correia, Murilo Missano Bell, João Vitor Robiatti Amorim, Jonas Queiroz, Daniel Pedronette, Ivan Rizzo Guilherme, Felipe Lima de Oliveira
| Challenge: | Lack of high-quality test collections challenges Information Retrieval (IR) in specialized domains. |
| Approach: | They compare supervised classifiers against zero-shot Large Language Models for automated relevance annotation in the oil and gas industry using human expert judgments as a benchmark. |
| Outcome: | The proposed classifier outperforms LLMs in the oil and gas industry using human expert judgments. |