Papers with automated design
Learning Emphasis Selection for Written Text in Visual Media from Crowd-Sourced Label Distributions (P19-1)
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Amirreza Shirani, Franck Dernoncourt, Paul Asente, Nedim Lipka, Seokhwan Kim, Jose Echevarria, Thamar Solorio
| Challenge: | Visual communication relies heavily on images and short texts to grab a viewer's attention and convey a message in the most efficient way. |
| Approach: | They propose a model that employs end-to-end label distribution learning on crowd-sourced data and predicts a selection distribution, capturing the inter-subjectivity and ambiguity of the input. |
| Outcome: | The proposed model captures the inter-subjectivity and ambiguity of the input and can be transformed to single-label learning by mapping labels to absolute labels via majority voting. |
MoPS: Modular Story Premise Synthesis for Open-Ended Automatic Story Generation (2024.acl-long)
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| Challenge: | Existing sources of story premises are limited by a lack of diversity, uneven quality, and high costs that make them difficult to scale. |
| Approach: | They propose a method which breaks down story premises into modules like background and persona for automated design and generation. |
| Outcome: | The proposed framework excels in diversity, fascination, completeness, and originality compared to those induced from large language models and captured from public datasets. |
Inefficiencies of Meta Agents for Agent Design (2025.findings-emnlp)
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| Challenge: | Recent work has automated the design of agentic systems using meta-agents . authors examine three key challenges in a common class of meta-gents. |
| Approach: | They examine how meta-agents learn across iterations and show performance improves with evolutionary approach. |
| Outcome: | The proposed meta-agents perform worse when iterating on multiple agents than human-designed agents. |