Hugging Face · 논문
SERO: Learning from Executable Oracle Continuations for Long-Horizon Agentic Reinforcement Learning
Hugging Face 일일 논문 목록에 오른 논문입니다 (arXiv 2610.19397).
원문 공개 요약 발췌
Long-horizon agentic RL is constrained by the futures visited by the current policy. When rollouts fail to reach useful behaviors, improved credit assignment cannot provide supervision for states and actions that were never encountered.원문 피드·공개 API 가 내보낸 소개 문구의 앞부분입니다.
출처
- 조직
- Hugging Face
- 소스
- Hugging Face 일일 논문
- 원문 제목
- SERO: Learning from Executable Oracle Continuations for Long-Horizon Agentic Reinforcement Learning
- 게시 시각
- (KST)
- 원문
- https://huggingface.co/papers/2610.19397