File size: 9,584 Bytes
4b3fed3 497fa38 4b3fed3 497fa38 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 | {
"name": "TempCompass",
"release_date": "2024-06-01",
"subsets": {
"multi_choice": {
"language": [
"en"
],
"modalities": [
"single_video_start"
],
"task_type": "multiple_choice_qa",
"score_pipeline": [
"exact-match",
"rule-match",
"llm-judge"
],
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/tempcompass/utils.py:115-172 (hand-crafted letter-match rules first; on failure ChatGPT judges Correct/Incorrect) + :480 (judge = gpt-3.5-turbo-1106) — mirrors official llyx97/TempCompass eval; vlmevalkit@vlmeval/dataset/tempcompass.py:63-260 (TempCompass_MCQ, DEFAULT_JUDGE chatgpt-1106) agrees.",
"note": "Official judge model gpt-3.5-turbo-1106. Official reports accuracy per temporal dimension (extra.dim) and overall average across the four task formats; per-sample scoring reproduces per-subset accuracy only."
},
"prompt_template": "<video>{{ question }}\nPlease directly give the best option:",
"mapping_from_source": {
"media": {
"from": "video_path",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"video_id": {
"from": "video_id"
},
"dim": {
"from": "dim"
}
},
"source": {
"format": "json",
"url": {
"train": "https://huggingface.co/datasets/lmms-lab/TempCompass"
}
}
},
"video_storage": {
"format": "files",
"media_root": "videos",
"notes": "410 videos from ShutterStock, distributed via lmms-lab/TempCompass HF repo. Includes original and conflicting (reversed/concatenated) videos for temporal perception testing."
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/tempcompass/_default_template_yaml (canonical per-subset post_prompts: multi-choice → 'Please directly give the best option:'; yes_no → 'Please answer yes or no:'; caption_matching → 'Please directly give the best option:')",
"notes": "Tier 4: lmms-eval TempCompass canonical per-subset evaluation prompts."
}
},
"yes_no": {
"language": [
"en"
],
"modalities": [
"single_video_start"
],
"task_type": "yes_no_qa",
"score_pipeline": [
"exact-match",
"rule-match",
"llm-judge"
],
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/tempcompass/utils.py:174-225 (extract_pred yes/no rule first; ChatGPT gpt-3.5-turbo-1106 judge fallback) — mirrors official llyx97/TempCompass; vlmevalkit@vlmeval/dataset/tempcompass.py:458-630 (TempCompass_YorN) agrees.",
"note": "Official judge model gpt-3.5-turbo-1106; official aggregation is per-dim + cross-format average."
},
"prompt_template": "<video>{{ question }}\nPlease answer yes or no:",
"mapping_from_source": {
"media": {
"from": "video_path",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"video_id": {
"from": "video_id"
},
"dim": {
"from": "dim"
}
},
"source": {
"format": "json",
"url": {
"train": "https://huggingface.co/datasets/lmms-lab/TempCompass"
}
}
},
"video_storage": {
"format": "files",
"media_root": "videos",
"notes": "410 videos from ShutterStock, distributed via lmms-lab/TempCompass HF repo. Includes original and conflicting (reversed/concatenated) videos for temporal perception testing."
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/tempcompass/_default_template_yaml (canonical per-subset post_prompts: multi-choice → 'Please directly give the best option:'; yes_no → 'Please answer yes or no:'; caption_matching → 'Please directly give the best option:')",
"notes": "Tier 4: lmms-eval TempCompass canonical per-subset evaluation prompts."
}
},
"caption_matching": {
"language": [
"en"
],
"modalities": [
"single_video_start"
],
"task_type": "multiple_choice_qa",
"score_pipeline": [
"exact-match",
"rule-match",
"llm-judge"
],
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/tempcompass/utils.py:227-277 (eval_rule deterministic caption-option matching first; ChatGPT gpt-3.5-turbo-1106 judge fallback) — mirrors official llyx97/TempCompass caption_matching eval.",
"note": "Options are full caption sentences embedded in the question text (no options dict); official judge model gpt-3.5-turbo-1106."
},
"prompt_template": "<video>{{ question }}\nPlease directly give the best option:",
"mapping_from_source": {
"media": {
"from": "video_path",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"video_id": {
"from": "video_id"
},
"dim": {
"from": "dim"
}
},
"source": {
"format": "json",
"url": {
"train": "https://huggingface.co/datasets/lmms-lab/TempCompass"
}
}
},
"video_storage": {
"format": "files",
"media_root": "videos",
"notes": "410 videos from ShutterStock, distributed via lmms-lab/TempCompass HF repo. Includes original and conflicting (reversed/concatenated) videos for temporal perception testing."
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/tempcompass/_default_template_yaml (canonical per-subset post_prompts: multi-choice → 'Please directly give the best option:'; yes_no → 'Please answer yes or no:'; caption_matching → 'Please directly give the best option:')",
"notes": "Tier 4: lmms-eval TempCompass canonical per-subset evaluation prompts."
}
},
"captioning": {
"language": [
"en"
],
"modalities": [
"single_video_start"
],
"task_type": "captioning",
"score_pipeline": [
"llm-judge"
],
"score_params": {
"rubric": "binary",
"official_judge_model": "gpt-3.5-turbo-1106"
},
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/tempcompass/utils.py:280-345 + :409 (every generated caption is graded by ChatGPT: the judge reads the caption and answers the row's mc_question; rating = 1 iff the judge's choice equals mc_answer) — official llyx97/TempCompass caption-generation eval.",
"note": "Official protocol requires per-row mc_question and mc_answer; the mm-eval mapping keeps only answer/video_id/dim. The published answer column verified (captioning/data.json, 2026-07-07) to carry the mc_answer in letter+text form (e.g. 'C. pushing bikes up a hill'), but mc_question is NOT shipped — as published, the official caption-matching judge prompt cannot be reconstructed without re-fetching mc_question from lmms-lab/TempCompass. Not caption_metrics (no CIDEr/BLEU): grading is LLM-QA-based, binary per sample."
},
"prompt_template": "<video>{{ question }}",
"mapping_from_source": {
"media": {
"from": "video_path",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"video_id": {
"from": "video_id"
},
"dim": {
"from": "dim"
}
},
"source": {
"format": "json",
"url": {
"train": "https://huggingface.co/datasets/lmms-lab/TempCompass"
}
}
},
"video_storage": {
"format": "files",
"media_root": "videos",
"notes": "410 videos from ShutterStock, distributed via lmms-lab/TempCompass HF repo. Includes original and conflicting (reversed/concatenated) videos for temporal perception testing."
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/tempcompass/_default_template_yaml (captioning task uses bare video+question)",
"notes": "Tier 4: lmms-eval TempCompass captioning canonical prompt (no scaffold)."
}
}
}
} |