Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
Tags:
academic-poster-generation
instruction-tuning
text-generation
document-understanding
poster-generation
License:
Release Manifest
This is the public evaluation-code entry for PosterEval-style poster metrics.
Included
evaluate_structural_pptx.py: PPTX evaluator forOve,Ali, andOfl.prepare_pptx_autofit.py: optional helper for materializing PPTX text-frame autofit geometry before structural evaluation.prepare_ir.py: VLM-based IR generation from poster images.evaluate_semantic_ir.py: evaluator forOrder,Completeness,LTA, andClaim F1.openrouter_client.py: OpenAI-compatible OpenRouter JSON client.qwen3_vl_embedding.py: lightweight local wrapper used byLTA.download_qwen3_vl_embedding.py: helper for downloadingQwen/Qwen3-VL-Embedding-2Bintomodels/modelscope/.prompts/: public prompts for content IR, figure IR, and claim-pair scoring.configs/semantic_ir.example.json: generic placeholder config for content metrics.requirements.txt: base Python dependency list.
Excluded
- Raw paper PDFs, poster PPTX files, rendered poster images, and datasets.
- API keys, private environment files, local workspace paths, and runtime artifacts.
- Paper-specific result tables or internal run outputs.