Papers by Faiaz Rahman

2 papers
DART: Open-Domain Structured Data Record to Text Generation (2021.naacl-main)

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Challenge: Data-to-text annotations can be costly when dealing with tables with nontrivial structures.
Approach: They propose a procedure for extracting semantic triples from tables that encodes their structures by exploiting table headers and table title.
Outcome: The proposed method exploits the semantic dependencies between table headers and title to extract semantic triples from tables.
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining (2021.acl-long)

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Challenge: Abstractive text summarization has primarily focused on modeling news articles . lack of standardized datasets for summarizing online conversations is a major problem .
Approach: They propose to crowdsource four new datasets for summarizing online conversations . they incorporate argument mining through graph construction to directly model issues, viewpoints, and assertions present in a conversation.
Outcome: The proposed models are compared against widely-used conversation summarization datasets and show comparable or improved results.

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