arXiv (All)
open access
Conditional Generation of Creative Chess Puzzles with Diffusion Models
While modern language models demonstrate impressive generative capabilities, they often struggle with constrained, counter-intuitive creative tasks. To address this limitation, we explore chess puzzle generation as a rigorous testbed for computational creativity and reasoning, a domain where alterin
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Measuring Similarity between Artistic and AI Generated Images using Siamese Neural Networks#792920
- Measuring Similarity between Artistic and AI Generated Images using Siamese Neural Networks#788916
- DesigNet: Learning to Draw Vector Graphics as Designers Do#985040
- Learning to Predict Future-Aligned Research Proposals with Language Models#1118504
- TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval#414142
Record · ID 1143178
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive