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episode_index
int32
frame_index
int32
A
int8
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int8
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int8
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int8
conf
float32
valid
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End of preview. Expand in Data Studio

ALLEX 압축 가능성 라벨 (v1_v2_v3_v4)

GR00T-N1.7 ALLEX 데모 320 에피 · 48,086 청크에 대해, 각 순간의 모션을 얼마나 솎아낼 수 있는지를 VLM 으로 매긴 라벨.

만든 방법

  • 판정기 gemini-3.8-flash (thinkingLevel low), 온도 0
  • 입력: 그 순간의 좌·우 ego 카메라 2장 + 지시문 + 계획된 액션에서 계산한 사실
  • 출력: 문항 AD 를 15 등급으로. prompts/allex.txt 가 나간 전문 그대로다
  • SYSTEM 메시지를 쓰지 않는다. role: user 하나이고 GUIDANCE 가 본문 머리에 온다
  • 청크 길이 16, stride 16. 라벨된 청크가 에피소드를 겹침도 빈틈도 없이 타일링하므로 모든 프레임은 정확히 하나의 라벨된 청크 안에 들어간다. 다만 그것은 프레임 커버리지 이야기이고, 파일에 있는 행은 t ∈ {0, 16, 32, …} 뿐이다 -- 임의의 t 에서 시작하는 청크에는 라벨이 없다. 아래 "중간 시점" 참고

파일

labels/allex_v1_v2_v3_v4.parquet   48,086행 (v1_v2 27,872 + v3_v4 20,214)
labels/allex_v1_v2.parquet         앞선 판 (v1_v2 만)
prompts/allex.txt                  나간 전문
checks/allex.py                    부호·가중·conf 식

ep, f 에피소드 · 청크 시작 프레임
A~`D` 문항별 등급 1~5
conf 압축 가능성 0~1. 높을수록 압축 가능
split v1_v2 (ep < 160) / v3_v4
instr 지시문 (전 에피 동일)
one_handed, merge_demand_k2 계산 사실에 쓰인 값

conf

conf = (1 + Σ_safe w·g − Σ_risk w·g) / 2 ,   g = (등급−1)/4

부호와 가중은 checks/allex.py. 가중은 라벨링을 마친 뒤 실측 세 칸의 순서를 재현하도록 재적합한 값이다 (에피 LOO 홀드아웃 AUC 0.865).

판정기가 바뀌면 가중을 다시 잡아야 한다. 같은 문항에서도 Cosmos3-Nano 는 A .80/B .20, Sonnet 4.5 는 A .60/B .40 이 최적이었다.

중간 시점의 conf 는 채워 써야 한다

학습 표본을 16의 배수에서만 뽑는다면 아무것도 안 해도 된다. 그 밖에는 채워야 한다.

청크 [t, t+16)16k <= t < 16(k+1) 일 때 라벨된 두 블록에 걸친다 -- 블록 k 의 프레임 (16k+16-t) 개와 블록 k+1 의 프레임 (t-16k) 개를 가진다. 그래서 채우는 방법이 원리적으로 정해진다.

1. 겹침 비율 가중 선형보간 (기본 권장)

k = t // 16
w = (t - 16*k) / 16
conf_t = (1 - w) * conf[16*k] + w * conf[16*k + 16]

임의의 스무딩이 아니라 그 청크가 실제로 포함하는 프레임 비율로 평균낸 값이다. t = 16k 에서 원래 값으로 정확히 돌아가므로, 라벨 위에서 잡은 역치(tau)가 그대로 유지된다.

2. min(conf[16k], conf[16k+16]) — 보수적으로 갈 때

게이트에서 "압축해도 된다" 를 잘못 말하면 에피소드가 깨지고 "압축 안 한다" 를 잘못 말하면 속도만 손해다. 이 비대칭이 신경 쓰이면 두 블록의 최솟값을 쓴다. 대신 conf 분포가 아래로 밀리므로 tau 를 다시 잡아야 한다.

3. 최근접(floor(t/16)) 단독은 권하지 않는다. stride 16 이면 16프레임짜리 계단이 되고, 국면이 바뀌는 지점(운반 -> 내려놓기)에서 한 블록 통째로 틀린다.

복원 품질은 아직 안 쟀다. 같은 프로젝트의 robocasa 판은 stride 4 로 라벨하고 전 프레임 복원을 실측해 conf 상관 0.966 · 이진 재현율 95.1% 를 적었다. 이 판은 stride 16 이라 그보다 성길 수밖에 없고, 숫자는 재는 대로 여기에 적는다.

알아 둘 것

  • conf 는 정수 등급에서 나오므로 이산값 48개다. 역치를 잡을 때 값 위에 걸터앉지 않도록 한다.
  • 지시문이 320 에피 전부 같다. 태스크 구분은 이 라벨에 없다.
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