A plug-and-play framework for enhancing diversity in long-prompt image generation
Bo-Kai Ruan, Teng-Fang Hsiao, Ling Lo, Yi-Lun Wu, Hong-Han Shuai
| Qwen-Image |
|---|
 |
| +PromptMoG (Ours) |
 |
| +CADS |
 |
| +DiverseFlow |
 |
uv sync # load environment source .venv/bin/activate
We have provided the filtered dataset in data/lpd_bench. Users can also follow the following steps to generate the dataset themselves.
# Step 1: Generate a pool of long prompts python misc/dataset_gen/generate_long_prompt.py --num-prompts-for-topic 60 # Step 2: Filter the prompts python misc/dataset_gen/post_process_data.py --data-root data/lpd_bench --num_prompts_per_topic 60 --num_remain_per_topic 40
The outputs will be saved to data/lpd_bench/filtered.
Diversity Test
# Generate images ./scripts/gen_image.sh \ --dataset_type long \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/long_prompt ./scripts/gen_image.sh \ --dataset_type short \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/short_prompt_1 \ --first_top 1 ./scripts/gen_image.sh \ --dataset_type short \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/short_prompt_3 \ --first_top 3 # Score the diversity ./scripts/scoring_diversity.sh --output_root_dir outputs/long_prompt ./scripts/scoring_diversity.sh --output_root_dir outputs/short_prompt_1 ./scripts/scoring_diversity.sh --output_root_dir outputs/short_prompt_3
./scripts/gen_image.sh \
--dataset_type long \
--model_type pmog \
--prompt_root_dir data/lpd_bench \
--output_root_dir outputs/pmog
./scripts/scoring_diversity.sh --output_root_dir outputs/pmog
./scripts/scoring_lpd.sh --output_root_dir outputs/pmog| Model | Gamma | Num Mode | Sigma |
|---|---|---|---|
| Flux | 0.6 | 50 | 0.25 |
| Qwen | 0.85 | 50 | 0.25 |
Exploring the gamma
GAMMA_LIST=(0.1 0.35 0.6 0.85 1.1) for gamma in ${GAMMA_LIST[@]}; do ./scripts/ablation/gen_and_scoring_ablation.sh \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/ablation_gamma_flux_${gamma}_qwen_${gamma} \ --dataset_type long \ --model_type pmog \ --partial_num 8 \ --flux_gamma ${gamma} \ --qwen_gamma ${gamma} ./scripts/scoring_lpd.sh --output_root_dir outputs/ablation_gamma_flux_${gamma}_qwen_${gamma} done
Exploring the sigma
# [0, 0.25, 0.5, 0.75, 1.0] SIGMA_LIST=(0 0.25 0.5 0.75 1.0) for sigma in ${SIGMA_LIST[@]}; do ./scripts/ablation/gen_and_scoring_ablation.sh \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/ablation_sigma_flux_${sigma}_qwen_${sigma} \ --dataset_type long \ --model_type pmog \ --partial_num 8 \ --flux_sigma ${sigma} \ --qwen_sigma ${sigma} ./scripts/scoring_lpd.sh --output_root_dir outputs/ablation_sigma_flux_${sigma}_qwen_${sigma} done
Exploring the mode
NUM_MODE_LIST=(1 25 50 75 100) for num_mode in ${NUM_MODE_LIST[@]}; do ./scripts/ablation/gen_and_scoring_ablation.sh \ --prompt_root_dir data/lpd_bench \ --output_root_dir outputs/ablation_mode_flux_${num_mode}_qwen_${num_mode} \ --dataset_type long \ --model_type pmog \ --partial_num 8 \ --flux_num_mode ${num_mode} \ --qwen_num_mode ${num_mode} ./scripts/scoring_lpd.sh --output_root_dir outputs/ablation_mode_flux_${num_mode}_qwen_${num_mode} done
@inproceedings{promptmog, title={Diversifying Long Prompt Image Generation through Structured Prompt Embedding Space Sampling}, author={Ruan, Bo-Kai and Hsiao, Teng-Fang and Lo, Ling and Wu, Yi-Lun and Shuai, Hong-Han}, booktitle={BMVC}, year={2026} }