Zobrazeno 1 - 10
of 6 727
pro vyhledávání: '"Liu, PengFei"'
Aligning language models (LMs) with human preferences has become a key area of research, enabling these models to meet diverse user needs better. Inspired by weak-to-strong generalization, where a strong LM fine-tuned on labels generated by a weaker
Externí odkaz:
http://arxiv.org/abs/2410.18640
Autor:
Zhang, Shuning, Ye, Lyumanshan, Yi, Xin, Tang, Jingyu, Shui, Bo, Xing, Haobin, Liu, Pengfei, Li, Hewu
Memories, encompassing past inputs in context window and retrieval-augmented generation (RAG), frequently surface during human-LLM interactions, yet users are often unaware of their presence and the associated privacy risks. To address this, we propo
Externí odkaz:
http://arxiv.org/abs/2410.14931
While various vertical domain large language models (LLMs) have been developed, the challenge of automatically evaluating their performance across different domains remains significant. Current benchmark-based evaluation methods exhibit rigid, aimles
Externí odkaz:
http://arxiv.org/abs/2410.11507
Autor:
Qin, Yiwei, Li, Xuefeng, Zou, Haoyang, Liu, Yixiu, Xia, Shijie, Huang, Zhen, Ye, Yixin, Yuan, Weizhe, Liu, Hector, Li, Yuanzhi, Liu, Pengfei
This paper introduces a pioneering approach to artificial intelligence research, embodied in our O1 Replication Journey. In response to the announcement of OpenAI's groundbreaking O1 model, we embark on a transparent, real-time exploration to replica
Externí odkaz:
http://arxiv.org/abs/2410.18982
Autor:
Jiayang, Cheng, Chan, Chunkit, Zhuang, Qianqian, Qiu, Lin, Zhang, Tianhang, Liu, Tengxiao, Song, Yangqiu, Zhang, Yue, Liu, Pengfei, Zhang, Zheng
The rise of large language models (LLMs) has significantly influenced the quality of information in decision-making systems, leading to the prevalence of AI-generated content and challenges in detecting misinformation and managing conflicting informa
Externí odkaz:
http://arxiv.org/abs/2410.04068
Large language model pre-training has traditionally relied on human experts to craft heuristics for improving the corpora quality, resulting in numerous rules developed to date. However, these rules lack the flexibility to address the unique characte
Externí odkaz:
http://arxiv.org/abs/2409.17115
We extract the leading Fock-state light front wave functions (LF-LFWFs) of heavy flavor-asymmetric pseudoscalar mesons $D$, $B$ and $B_c$ from their Bethe-Salpeter wave functions based on Dyson-Schwinger equations approach, and study their leading tw
Externí odkaz:
http://arxiv.org/abs/2409.05098
Autor:
Ru, Dongyu, Qiu, Lin, Hu, Xiangkun, Zhang, Tianhang, Shi, Peng, Chang, Shuaichen, Jiayang, Cheng, Wang, Cunxiang, Sun, Shichao, Li, Huanyu, Zhang, Zizhao, Wang, Binjie, Jiang, Jiarong, He, Tong, Wang, Zhiguo, Liu, Pengfei, Zhang, Yue, Zhang, Zheng
Despite Retrieval-Augmented Generation (RAG) showing promising capability in leveraging external knowledge, a comprehensive evaluation of RAG systems is still challenging due to the modular nature of RAG, evaluation of long-form responses and reliabi
Externí odkaz:
http://arxiv.org/abs/2408.08067
The interplay of symmetry and topology in crystal solids has given rise to various elementary excitations as quasiparticles. Among these, those with significant Berry-phase-related transport responses are of particular interest. Here, we predict a ne
Externí odkaz:
http://arxiv.org/abs/2408.07887
Autor:
Zheng, Yuxiang, Sun, Shichao, Qiu, Lin, Ru, Dongyu, Jiayang, Cheng, Li, Xuefeng, Lin, Jifan, Wang, Binjie, Luo, Yun, Pan, Renjie, Xu, Yang, Min, Qingkai, Zhang, Zizhao, Wang, Yiwen, Li, Wenjie, Liu, Pengfei
The rapid growth of scientific literature imposes significant challenges for researchers endeavoring to stay updated with the latest advancements in their fields and delve into new areas. We introduce OpenResearcher, an innovative platform that lever
Externí odkaz:
http://arxiv.org/abs/2408.06941