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"version": "0.1.0-rc1",
"working_title": "OTC-Bench: Overlay–Target Confusion Benchmark",
"paper_title": "When Overlays Become Targets: Diagnosing Target–Distractor Confusion in Vision-Language Models",
"code_repository": "https://github.com/Seren666/OTC-Bench",
"data_repository": "https://huggingface.co/datasets/MortalSnow/OTC-Bench",
"targets": 800,
"pairs": 1600,
"stimuli": 6400,
"models": 6,
"model_answers": 38400,
"cohorts": {
"old_96": 96,
"old_204": 204,
"new_500": 500
},
"source": "COCO val2014",
"donor_instances": 16,
"donor_categories": 8,
"human_ratings": 3900,
"human_reviewed_pairs": 1300,
"cohort_semantics": {
"old_96": "Earlier development/expansion cohort",
"old_204": "Earlier extension, reviewed before new-500 freeze",
"new_500": "Later frozen target validation with existing donors; no donor-instance holdout"
},
"generation": "See cohort-specific configs. Most runs use temperature 0/top_p 1/max_tokens 32; LLaVA uses do_sample false; some old96 seeds differ.",
"public_image_redistribution": "not included; retrieve sources under their respective licenses and reconstruct",
"scoring": "format_tolerant default (pre-existing uniform sensitivity) plus preserved frozen mode"
}
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