Papers by Soumya Sharma
Realistic Data Augmentation Framework for Enhancing Tabular Reasoning (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches to constructing training data for Natural Language Inference (NLI) tasks are expensive and time consuming. |
| Approach: | They propose a semi-automated framework for data augmentation for tabular inference . framework generates hypothesis templates transferable to similar tables . authors say framework could generate human-like tabular examples . |
| Outcome: | The proposed framework generates human-like tabular inference examples . it is based on human-written constraints and premise paraphrasing . |
Financial Numeric Extreme Labelling: A dataset and benchmarking (2023.findings-acl)
Copied to clipboard
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)
Copied to clipboard
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 . |
Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs (D19-1)
Copied to clipboard
| Challenge: | Recent studies have shown that structured domain knowledge can be used for textual inference tasks in the medical domain. |
| Approach: | They propose to integrate structured domain knowledge into a knowledge graph for the Medical NLI task. |
| Outcome: | The proposed approach improves the baseline BioELMo architecture for the Medical NLI task. |
Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework (2021.findings-emnlp)
Copied to clipboard
| Challenge: | EMQAP is an automated question answering system for electronics devices . it uses a supervised multitask learning framework to identify the section in the E-manual where the answer can be found and the exact answer span within that section. |
| Approach: | They develop an algorithm to exploit data from E-manuals and pretrain RoBERTa on it. |
| Outcome: | The proposed algorithm improves ROUGE-L F1 scores over most competitive baseline. |