MihailSlutsky's picture
14 answer-correct multimodal trajectories + XSkill critique + human GT
f6191f6 verified
Raw
History Blame Contribute Delete
10.7 kB
{
"schema_version": 1,
"scope": "14 answer-correct rollouts from ViSTR skill_val (baseline / perception mode, qwen3-vl-plus)",
"annotator": "gaozhe (manual notes 2026-08-19) + reviewer cross-check",
"label_definitions": {
"process_false_positive": "answer correct but the reasoning depends on a false or fabricated premise",
"process_ok": "answer correct and the cited evidence supports the conclusion",
"gray_zone": "answer correct, no outright false premise, but the rubric is unverifiable / not generalisable, or annotators disagree"
},
"confidence_definitions": {
"high": "explicit manual note for this case",
"derived": "inferred from a manual note covering a cluster of cases",
"reviewer_only": "no manual note; reviewer judgement, needs a second annotator"
},
"counts": {
"process_false_positive": 5,
"gray_zone": 3,
"process_ok": 6
},
"caveats": [
"Single primary annotator; inter-annotator agreement not yet measured.",
"n=14 supports existence and taxonomy claims, not stable rates.",
"Reviewer and annotator initially disagreed on #148 (reviewer wrong) and #57 (reviewer stricter), so labels are revisable."
],
"annotations": [
{
"sample_id": "148",
"label": "process_false_positive",
"severity": "severe",
"confidence": "high",
"error_layer": "perception_structural",
"human_note_zh": "假阳性:“The block being removed is in the middle where it likely supports significant weight above it”这句话纯扯淡,Jenga稳定性取决于目标块抽走之后,剩余结构能不能稳定。首先这个块在高度的middle 但不在横层意义上的middle,其次抽走后,该层只剩一个边上的块了,所以无法支撑。",
"false_claim": "The block being removed is in the middle where it likely supports significant weight above it",
"why_wrong": "Jenga stability depends on whether the REMAINING blocks in that layer can support the load. The target is mid-height but off-centre within its layer; after removal only one edge block remains in that layer.",
"reviewer_crosscheck": "Frames confirm the hand pulls an off-centre block. The solver applied a generic 'tall tower + gaps + middle block' template with no layer-level structural analysis. Reviewer initially mis-rated this as sound; the manual note is correct."
},
{
"sample_id": "156",
"label": "process_false_positive",
"severity": "moderate",
"confidence": "high",
"error_layer": "reasoning",
"human_note_zh": "假阳性,但没148严重。“塔身没有出现摇晃或不稳定的迹象,并且在整个视频序列中塔身都保持着其结构,因此我预测塔身将保持稳定”扯淡了。但是“剩余块体的排列和平衡”这个rubric是对的。",
"false_claim": "no wobbling observed during the video, therefore the tower will remain stable after removal",
"why_wrong": "The video ends before the block is fully removed, so absence of wobble carries no information about post-removal stability. The valid rubric is the arrangement/balance of the remaining blocks.",
"reviewer_crosscheck": "Confirmed. The solver also cited 'alternating colour pattern implies good weight distribution', which is not a load-bearing property."
},
{
"sample_id": "110",
"label": "process_false_positive",
"severity": "moderate",
"confidence": "high",
"error_layer": "reasoning",
"human_note_zh": "ai 自己总结的rubric 不对,导致是假阳性。同样一套rubric 用在 #109 就错了。",
"false_claim": "centroid drift across frames therefore the vehicle shows subtle movement",
"why_wrong": "The rubric has no ego-motion compensation, so apparent centroid drift conflates camera motion with target motion. It is not generalisable.",
"reviewer_crosscheck": "Empirically confirmed on #109 (same subtask, same rubric, answer wrong). Raw tracks: #110 obj_0 dx=+0.287 (large, genuinely moving) vs #109 obj_0 dx=-0.051 with a global mean of -0.007 across 7 tracked vehicles, i.e. a small residual the rubric cannot resolve."
},
{
"sample_id": "23",
"label": "process_false_positive",
"severity": "severe",
"confidence": "high",
"error_layer": "data_fabrication",
"human_note_zh": "这几个 case 感觉完全就是幻觉了,“目标球确实进入了袋口”,显然没有。其次问题问的是将来时的“会不会”,他给答成完成时了。边界框小+落到球袋 这个完全是幻觉rubric了,可执行性也贼差。",
"false_claim": "the ball's bbox becomes very small and it is positioned at the corner, i.e. it disappeared into the pocket",
"why_wrong": "Fabricated: obj_4 bbox area is 0.00076 at the last frame vs 0.0007 at the first (no contraction); final centroid (0.733, 0.862) is not a corner; visibility stays 1.0 through the final frame. A 4-frame tracking gap (frames 20-23) is followed by 49 more tracked frames (24-72), so nothing was pocketed. Also a tense error: the task asks for a prediction, the solver reported a completed event.",
"reviewer_crosscheck": "Verified against workspace tracks/tracks.json. Additionally the tracking JSON the solver received was TRUNCATED (51KB mid-section, no opening brace), so part of its cited data was never visible to it."
},
{
"sample_id": "26",
"label": "process_false_positive",
"severity": "moderate",
"confidence": "derived",
"error_layer": "data_fabrication",
"human_note_zh": "(覆盖于“# 23-29 这几个 case 感觉完全就是幻觉了”这条批注)",
"false_claim": "balls clustered at the pocket location in the final frames imply the target ball goes in",
"why_wrong": "Same hallucinated rubric family as #23 (proximity/size treated as pocket entry) plus the future-vs-completed tense conflation.",
"reviewer_crosscheck": "Frame inspection is real, but the pocket-entry inference rests on the same unvalidated rubric."
},
{
"sample_id": "27",
"label": "gray_zone",
"severity": "unclear",
"confidence": "derived",
"error_layer": "reasoning",
"human_note_zh": "(“# 23-29 这几个 case”按 id 区间覆盖了 27,但该条批注的具体指控针对答 Yes 的案例;27 答 No。需人工确认。)",
"false_claim": "pending explicit confirmation",
"why_wrong": "Manual note covers the billiards cluster as hallucination-prone; the specific complaint (claiming the ball went in) does not apply to this No answer. Needs a second pass.",
"reviewer_crosscheck": "Our tool-grounded critic flagged direction errors in obj_0/obj_4 motion claims and a target-ball misidentification, which supports a FP label, but this was not independently confirmed by the human annotator."
},
{
"sample_id": "63",
"label": "process_ok",
"severity": null,
"confidence": "high",
"error_layer": null,
"human_note_zh": "模型知道用 tracking 去间接估计位姿,这很好,这是我人都想不出来的,说明有自进化的潜力。但当相机消失时,model 是不是可以用新的tracking 标记物去指示自己的方位呢?(当然 这不构成指导意见)",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Uses the exit-edge rule (target leaves via the left edge then vanishes therefore back-left). Consistent with the tracking data."
},
{
"sample_id": "57",
"label": "process_ok",
"severity": null,
"confidence": "high",
"error_layer": null,
"human_note_zh": "建议同 63",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Multi-evidence convergence (bbox shrink + centroid to the left edge + depth). One overstatement: 'washer remains on the left throughout' while the track starts at centroid x=0.837 (right side). Numbers cited are imprecise (final width 0.016 vs actual 0.005) but the trend and conclusion hold."
},
{
"sample_id": "59",
"label": "process_ok",
"severity": null,
"confidence": "high",
"error_layer": null,
"human_note_zh": "建议同 63",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Sound, though it announced a frame-sampling verification step and then concluded without doing it."
},
{
"sample_id": "52",
"label": "process_ok",
"severity": null,
"confidence": "high",
"error_layer": null,
"human_note_zh": "建议同 63",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Last-seen-side plus camera-egress reasoning, consistent with the data."
},
{
"sample_id": "120",
"label": "gray_zone",
"severity": null,
"confidence": "high",
"error_layer": null,
"human_note_zh": "推理合理,但最终还是纯借助了 VLM 本身的判断能力,而没有形成一套可验证的rubric。",
"false_claim": null,
"why_wrong": "Conclusion follows from frame comparison, but no quantified, reusable criterion was produced (how much displacement counts as faster, how perspective is handled).",
"reviewer_crosscheck": "Agreed: correct answer, low rubric executability."
},
{
"sample_id": "81",
"label": "process_ok",
"severity": null,
"confidence": "reviewer_only",
"error_layer": null,
"human_note_zh": "(人工核验笔记未覆盖)",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Real tracking data plus frame cross-check. Pixel conversions are wrong (claimed 8px/37px vs actual ~15px/~47px) but direction and magnitude class are unaffected."
},
{
"sample_id": "96",
"label": "process_ok",
"severity": null,
"confidence": "reviewer_only",
"error_layer": null,
"human_note_zh": "(人工核验笔记未覆盖)",
"false_claim": null,
"why_wrong": null,
"reviewer_crosscheck": "Under-reports the displacement magnitude by ~10x (claims final x=0.419, actual 0.384), but the error direction strengthens rather than undermines the 'movement exists' conclusion."
},
{
"sample_id": "71",
"label": "gray_zone",
"severity": "reviewer_flagged",
"confidence": "reviewer_only",
"error_layer": "reasoning",
"human_note_zh": "(人工核验笔记未覆盖)",
"false_claim": "the object drifted right-to-left and exited, therefore it is behind and to the RIGHT of the camera",
"why_wrong": "Under pure translation, exiting via the left edge implies back-LEFT. The mapping contradicts #63, which derived back-left from the same evidence pattern. Answer happened to match ground truth (camera likely yawed).",
"reviewer_crosscheck": "Tracking quality is also poor: 62/408 frames have the target, final-frame confidence is the -10000 sentinel. Needs human adjudication."
}
]
}