This article explains the key points of PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost. 2026-03-22 (arXiv) Yi, Junkeun, Mosk-Aoyama, Damon, Huang, Baihe, Gala, Ritu, Wang, Charles, Devare, Sugam Dipak, Bhardwaj, Khushi, Gupta, Abhibha, Kuchaiev, Oleksii, Jiao, Jiantao, et al. NVIDIA, UC Berkeley Paper Read this article in Korean...

이번 글에서는 PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost 논문의 핵심 포인트만 간단히 정리한다. 2026년 3월 22일(Arxiv) Yi, Junkeun, Mosk-Aoyama, Damon, Huang, Baihe, Gala, Ritu, Wang, Charles, Devare, Sugam Dipak, Bhardwaj, Khushi, Gupta, Abhibha, Kuchaiev, Oleksii, Jiao, Jiantao, et al. NVIDIA, UC Berkeley 논문 링크 영문판 보기 요약...

This article explains the key points of Efficient Exploration at Scale. 2026-03-18 (arXiv) Asghari, Seyed Mohammad, Chute, Chris, Dwaracherla, Vikranth, Lu, Xiuyuan, Jafarnia, Mehdi, Minden, Victor, Wen, Zheng, Van Roy, Benjamin. Google DeepMind Paper Read this article in Korean Summary Efficient Exploration at Scale studies how to reduce the preference-label...

이번 글에서는 Efficient Exploration at Scale 논문의 핵심 포인트만 간단히 정리한다. 2026년 3월 18일(Arxiv) Asghari, Seyed Mohammad, Chute, Chris, Dwaracherla, Vikranth, Lu, Xiuyuan, Jafarnia, Mehdi, Minden, Victor, Wen, Zheng, Van Roy, Benjamin. Google DeepMind 논문 링크 영문판 보기 요약 Efficient Exploration at Scale은 LLM 정렬에 필요한 선호도 레이블을 줄이는 방법을...

This article explains the key points of Online Experiential Learning for Language Models. 2026-03-17 (arXiv) Ye, Tianzhu, Dong, Li, Dong, Qingxiu, Wu, Xun, Huang, Shaohan, Wei, Furu. Microsoft Research Paper Project Page Read this article in Korean Summary Online Experiential Learning (OEL) turns deployment trajectories into model updates without reward...