Papers with Realism
KidsArtBench: Multi-Dimensional Children’s Art Evaluation with Attribute-Aware MLLMs (2026.eacl-long)
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| Challenge: | Multimodal Large Language Models (MLLMs) show impressive capabilities across visual–language tasks, but their capacity to evaluate artistic expression remains limited. |
| Approach: | They propose an attribute-specific multi-LoRA approach where each attribute corresponds to a distinct evaluation dimension in the scoring rubric. |
| Outcome: | The proposed approach increases correlation from 0.468 to 0.653 on Qwen2.5-VL-7B, with the largest gains on perceptual dimensions and narrowed gaps on higher-order attributes. |
Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards (2026.findings-acl)
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Luis Lara, Aristides Milios, ZhiHao Luo, Aditya Sharma, Ge Ya Luo, Christopher Beckham, Florian Golemo, Christopher Pal
| Challenge: | Existing generative models focus on respecting the requested connectivity between rooms, but do not support generating floor plans that respect numerical constraints. |
| Approach: | They propose a text-based approach that fine-tunes a large language model on real plans and applies reinforcement learning with verifiable rewards to improve adherence to topological and numerical constraints. |
| Outcome: | The proposed model outperforms existing methods on Realism, Compatibility, Diversity metrics. |