feat(report): 로봇 데이터 4인터페이스 — KO+EN 신규 리포트 - #1285
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VLA·월드 모델 다음에 필요한 네 개의 번역 장치(자동 라벨링·리타게팅· 물리 기반 3D 추론·성공 판정)를 논문 밖 독립 근거로 검증. - KO: 로봇이 못 배우는 건 데이터가 없어서가 아니다 - EN: Robots Aren't Short on Data. They're Short on Translation. - 참고문헌 44건(CSL-JSON), 유튜브 해설 영상 포함 - OG 이미지 생성, articles.d 사이드카(provenance 포함), SEO 4계층 검증 통과 Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
…-youtu-be-tnjilbvwex4-si-y-mk160qgo-msnzesrj
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Summary
유튜브 해설 영상(https://youtu.be/tnjILbVweX4)이 다루는 로봇 학습 데이터 관련 논문·주제를 심층 조사한 리포트. VLA·월드 모델 다음 단계에서 필요한 네 개의 데이터 번역 장치(자동 라벨링, 리타게팅, 물리 기반 3D 추론, 성공 판정)의 성숙도와 한계를 논문 밖 독립 근거(44건 참고문헌, 유튜브 원 영상 포함)로 검증했다.
변경 파일
report/robot-data-interfaces-beyond-vla/ko/index.htmlreport/robot-data-interfaces-beyond-vla/en/index.htmlreport/robot-data-interfaces-beyond-vla/{ko,en}/image/report/robot-data-interfaces-beyond-vla/references.json(44건, YouTube 원 영상 포함)report/robot-data-interfaces-beyond-vla/sns/index.mdhistory/changelog.jsonlappendTest plan
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