Researchy Questions introduces a dataset of complex, non-factoid questions challenging LLMs. It highlights the need for multi-perspective queries and emphasizes the importance of decomposition in answering such questions effectively. The study evaluates different question-answering techniques and provides insights into user behavior in search sessions.
The dataset consists of real user queries from search logs filtered to be non-factoid and decompositional. It aims to push the boundaries of QA by focusing on unknown unknowns and requiring substantial research effort to synthesize answers. By analyzing user interactions with these questions, the study sheds light on the complexity involved in handling multi-perspective queries.
Furthermore, the evaluation of answer techniques reveals that decomposition methods lead to improved performance on Researchy Questions compared to direct answering. The study also discusses limitations, ethical considerations, and future directions for utilizing the dataset effectively in advancing question-answering systems.
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by Corby Rosset... às arxiv.org 02-29-2024
https://arxiv.org/pdf/2402.17896.pdfPerguntas Mais Profundas