2 papers
cs.AI2026
R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search
João Pedro Gandarela, Thiago Rios, Stefan Menzel +1
Large language models (LLMs) are fluent on open-ended tasks, yet in agentic settings, where a system must plan, use tools, and act over extended horizons, fluency does not ensure r…
cs.CV2024
Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models
Bingchen Liu, Ehsan Akhgari, Alexander Visheratin +7
We introduce Playground v3 (PGv3), our latest text-to-image model that achieves state-of-the-art (SoTA) performance across multiple testing benchmarks, excels in graphic design abi…