Papers by Afreen Shaikh
Financial Numeric Extreme Labelling: A dataset and benchmarking (2023.findings-acl)
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Soumya Sharma, Subhendu Khatuya, Manjunath Hegde, Afreen Shaikh, Koustuv Dasgupta, Pawan Goyal, Niloy Ganguly
| Challenge: | In 2019, the SEC mandates that all public companies file periodic financial statements that should contain numerals annotated with a particular label. |
| Approach: | They propose to use a dataset to automate the assignment of a label to a particular numeral span in a sentence from an extremely large label set. |
| Outcome: | The proposed solution outperforms the previous approaches but is less frequent than the pipeline solution. |
ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts (2022.emnlp-main)
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Rajdeep Mukherjee, Abhinav Bohra, Akash Banerjee, Soumya Sharma, Manjunath Hegde, Afreen Shaikh, Shivani Shrivastava, Koustuv Dasgupta, Niloy Ganguly, Saptarshi Ghosh, Pawan Goyal
| Challenge: | ECTSum is a dataset for bullet-point summarization of earnings calls hosted by publicly traded companies. |
| Approach: | They propose a dataset with transcripts of earnings calls and bullet point summaries derived from Reuters articles. |
| Outcome: | The proposed dataset compares transcripts of earnings calls hosted by publicly traded companies with experts-written bullet point summaries derived from Reuters articles . |