Summary of Agents’ Room: Narrative Generation Through Multi-step Collaboration, by Fantine Huot et al.
Agents’ Room: Narrative Generation through Multi-step Collaboration
by Fantine Huot, Reinald Kim Amplayo, Jennimaria Palomaki, Alice Shoshana Jakobovits, Elizabeth Clark, Mirella Lapata
First submitted to arxiv on: 3 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG); Multiagent Systems (cs.MA)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach, Agents’ Room, is proposed for generating compelling fiction using large language models (LLMs). This framework breaks down narrative writing into subtasks handled by specialized agents, rather than relying on intricate prompting. To demonstrate the method’s effectiveness, a high-quality dataset, Tell Me A Story, is introduced, featuring complex prompts and human-written stories. Additionally, a novel evaluation framework is designed to assess long narratives. Experimental results show that Agents’ Room generates preferred stories compared to baseline systems, leveraging collaboration and specialization to decompose the complex task. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine writing a story without needing to think of every detail! A team came up with a new way to help computers generate exciting stories using “specialized agents” that work together. They created a special dataset called Tell Me A Story, filled with interesting prompts and completed stories written by humans. To see how well this works, they developed a unique way to measure the quality of these generated stories. The result? Computers can create stories that are just as good as those written by people! |
Keywords
» Artificial intelligence » Prompting