May 14, 2024, 4:42 a.m. | Subhendu Khatuya, Koushiki Sinha, Niloy Ganguly, Saptarshi Ghosh, Pawan Goyal

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.06669v1 Announce Type: cross
Abstract: While automatic summarization techniques have made significant advancements, their primary focus has been on summarizing short news articles or documents that have clear structural patterns like scientific articles or government reports. There has not been much exploration into developing efficient methods for summarizing financial documents, which often contain complex facts and figures. Here, we study the problem of bullet point summarization of long Earning Call Transcripts (ECTs) using the recently released ECTSum dataset. We leverage …

abstract articles arxiv call clear cs.ce cs.cl cs.ir cs.lg documents earnings earnings call exploration financial focus government patterns reports scientific summarization summarizing transcripts type while

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