EmoGenie: Benchmarking and Evaluating Expressed and Evoked Emotion in T2I Generation with MLLMs
cs.CV
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: Comments: Corresponding author: Xiongkuo Min. Equal contribution: Zixuan Xing and Lancheng Gao
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
- Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
- E$^3$mo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment
- EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment
- Emotion-Qwen: A Unified Framework for Emotion and Vision Understanding
- AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
- InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
- Qwen-Image Technical Report
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
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