PublicHearingBR: A Brazilian Portuguese Dataset of Public Hearing Transcripts for Summarization of Long Documents
원문 초록
This paper introduces PublicHearingBR, a Brazilian Portuguese dataset designed for summarizing long documents. The dataset consists of transcripts of public hearings held by the Brazilian Chamber of Deputies, paired with news articles and structured summaries containing the individuals participating in the hearing and their statements or opinions. The dataset supports the development and evaluation of long document summarization systems in Portuguese. Our contributions include the dataset, a hybrid summarization system to establish a baseline for future studies, and a discussion on evaluation metrics for summarization involving large language models, addressing the challenge of hallucination in the generated summaries. As a result of this discussion, the dataset also provides annotated data that can be used in Natural Language Inference tasks in Portuguese.
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A MISMATCHED Benchmark for Scientific Natural Language Inference
CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection
ARC: Argument Representation and Coverage Analysis for Zero-Shot Long Document Summarization with Instruction Following LLMs
Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model
Hallucinate at the Last in Long Response Generation: A Case Study on Long Document Summarization
Document Attribution: Examining Citation Relationships using Large Language Models
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