Papers by Aviral Joshi
An efficient method for Natural Language Querying on Structured Data (2023.acl-industry)
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| Challenge: | a new approach to NLQ on structured data is based on text-to-SQL type semantic parsing . domain classification, domain classification and domain classification are the main tasks . semantic parsed queries are less common when information is in structured form . |
| Approach: | They propose an efficient and reliable approach to natural language Querying on databases . they use domain classification, domain classification and slot/entity extraction to query a DB . |
| Outcome: | The proposed approach simplifies the NLQ on structured data problem to the following "bread and butter" tasks. |
When and how to paraphrase for named entity recognition? (2023.acl-long)
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Saket Sharma, Aviral Joshi, Yiyun Zhao, Namrata Mukhija, Hanoz Bhathena, Prateek Singh, Sashank Santhanam
| Challenge: | Named entity recognition (NER) is a key component underpinning many industrial pipelines for a variety of downstream applications. |
| Approach: | They propose to use back translation to annotate entity spans in generations and propose a paraphraser with a larger dataset. |
| Outcome: | The proposed method improves NER performance across different datasets with gold annotations and paraphrasing strength. |