Summary of Plants: a Novel Problem and Dataset For Summarization Of Planning-like (pl) Tasks, by Vishal Pallagani et al.
PLANTS: A Novel Problem and Dataset for Summarization of Planning-Like (PL) Tasks
by Vishal Pallagani, Biplav Srivastava, Nitin Gupta
First submitted to arxiv on: 18 Jul 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 presents a new direction in text summarization by introducing a planning-like (PL) task summarization problem. Unlike traditional summarization, PL tasks involve generating a series of actions to achieve specific goals, such as workflows or travel plans. The authors create a novel dataset and provide a baseline method for generating PL summaries. They evaluate their approach using quantitative metrics and qualitative user studies, comparing it to large language models. This work has the potential to revitalize research in summarization, which some consider a solved problem. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making computers better at understanding how things are done. Right now, computers are great at reading books or articles, but they’re not very good at helping us make plans, like planning a trip or following a recipe. The researchers created a new challenge called “planning-like” tasks and made a special dataset to test their ideas. They also developed a way for computers to summarize these plans in a helpful way. They tested their method and compared it to other ways that computers can summarize text. This work could help us make computers more useful in our daily lives. |
Keywords
» Artificial intelligence » Summarization
