In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models
The paper explores the potential of large Vision-Language Models (VLMs) to replicate the open-ended creative processes exemplified by Picbreeder. It highlights the differences in output between AI-driven and human-driven creative processes, focusing on metrics such as complexity and novelty. The authors investigate factors that may influence these differences, including exploratory noise and behavioral diversity among agents.
- ▪The study aims to understand if artificial agents can achieve open-ended discovery similar to humans.
- ▪Picbreeder serves as a model for human-driven open-ended search, generating diverse images through collaborative evolution.
- ▪The research identifies qualitative differences in outputs between VLMs and human users, analyzing them through various metrics.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.23908 |
| Publication time | Tue, 26 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-26T04:07:43.013Z |
| Last seen | 2026-05-26T04:07:43.013Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 650f_E54C9a- |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.23908 (cs) [Submitted on 1 Apr 2026] Title:In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models Authors:Sam Earle, Kay Arulkumaran, Andrew Dai, Akarsh Kumar, Julian Togelius, Sebastian Risi View a PDF of the paper titled In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models, by Sam Earle and 5 other authors View PDF HTML (experimental) Abstract:We are in the midst of large-scale industrial and academic efforts to automate the processes of scientific, technological and creative production through AI-driven assistants.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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