Summary of Systematic Exploration Of Dialogue Summarization Approaches For Reproducibility, Comparative Assessment, and Methodological Innovations For Advancing Natural Language Processing in Abstractive Summarization, by Yugandhar Reddy Gogireddy et al.
Systematic Exploration of Dialogue Summarization Approaches for Reproducibility, Comparative Assessment, and Methodological Innovations for Advancing Natural Language Processing in Abstractive Summarization
by Yugandhar Reddy Gogireddy, Jithendra Reddy Gogireddy
First submitted to arxiv on: 21 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the reproducibility of dialogue summarization models in natural language processing (NLP). Specifically, it explores the discrepancies between original studies and reproduced results using Hierarchical Memory Networks (HMNet) and Pointer-Generator Networks (PGN) variants. The study focuses on the AMI dataset and assesses the informativeness and quality of generated summaries through human evaluation, which introduces subjectivity and variability. To mitigate this issue, the paper evaluates the sample standard deviation of 0.656 in Dataset 1, indicating moderate data dispersion around the mean. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Dialogue summarization is a crucial part of NLP that aims to condense conversational content into concise summaries. This paper tries to reproduce previous studies on dialogue summarization using different models like HMNet and PGN variants. They use the AMI dataset and compare their results with the original findings. The study also looks at how well these models do in generating good summaries. |
Keywords
» Artificial intelligence » Natural language processing » Nlp » Summarization
