This article explains the key points of SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge. 2025-09-09 (arXiv) Haas, Lukas, Yona, Gal, D’Antonio, Giovanni, Goldshtein, Sasha, Das, Dipanjan. Google DeepMind, Google Research Paper Project Page Read this article in Korean Summary SimpleQA Verified addresses unreliable evaluation of large language...

이번 글에서는 SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge 논문의 핵심 포인트만 간단히 정리한다. 2025년 9월 9일(Arxiv) Haas, Lukas, Yona, Gal, D’Antonio, Giovanni, Goldshtein, Sasha, Das, Dipanjan. Google DeepMind, Google Research 논문 링크 Project Page 영문판 보기 요약 SimpleQA Verified는 단답형 사실성 벤치마크인 SimpleQA의 잘못된 기준 답변,...

This article explains the key points of Parallel-R1: Towards Parallel Thinking via Reinforcement Learning. 2025-09-09 (arXiv) Zheng, Tong, Zhang, Hongming, Yu, Wenhao, Wang, Xiaoyang, Dai, Runpeng, Liu, Rui, Bao, Huiwen, Huang, Chengsong, Huang, Heng, Yu, Dong. Tencent AI Lab Seattle, University of Maryland, College Park, University of North Carolina at...

이번 글에서는 Parallel-R1: Towards Parallel Thinking via Reinforcement Learning 논문의 핵심 포인트만 간단히 정리한다. 2025년 9월 9일(Arxiv) Zheng, Tong, Zhang, Hongming, Yu, Wenhao, Wang, Xiaoyang, Dai, Runpeng, Liu, Rui, Bao, Huiwen, Huang, Chengsong, Huang, Heng, Yu, Dong. Tencent AI Lab Seattle, University of Maryland, College Park, University of North Carolina...

This article explains the key points of Language Self-Play For Data-Free Training. 2025-09-09 (arXiv) Kuba, Jakub Grudzien, Gu, Mengting, Ma, Qi, Tian, Yuandong, Mohan, Vijai, Chen, Jason. Meta Superintelligence Labs, UC Berkeley Paper Read this article in Korean Summary Language-model post-training, further optimization of an already trained model, depends on...