Zobrazeno 1 - 10
of 14 565
pro vyhledávání: '"jiang, Nan"'
Large language models (LLMs) have achieved high accuracy, i.e., more than 90% pass@1, in solving Python coding problems in HumanEval and MBPP. Thus, a natural question is, whether LLMs achieve comparable code completion performance compared to human
Externí odkaz:
http://arxiv.org/abs/2410.21647
Web development involves turning UI designs into functional webpages, which can be difficult for both beginners and experienced developers due to the complexity of HTML's hierarchical structures and styles. While Large Language Models (LLMs) have sho
Externí odkaz:
http://arxiv.org/abs/2410.18362
Real-world applications of reinforcement learning often involve environments where agents operate on complex, high-dimensional observations, but the underlying (''latent'') dynamics are comparatively simple. However, outside of restrictive settings s
Externí odkaz:
http://arxiv.org/abs/2410.17904
Autor:
Chen, Jianfa, Shen, Emily, Bavalatti, Trupti, Lin, Xiaowen, Wang, Yongkai, Hu, Shuming, Subramanyam, Harihar, Vepuri, Ksheeraj Sai, Jiang, Ming, Qi, Ji, Chen, Li, Jiang, Nan, Jain, Ankit
Robust content moderation classifiers are essential for the safety of Generative AI systems. Content moderation, or safety classification, is notoriously ambiguous: differences between safe and unsafe inputs are often extremely subtle, making it diff
Externí odkaz:
http://arxiv.org/abs/2410.14881
Cache-assisted ultra-dense mobile edge computing (MEC) networks are a promising solution for meeting the increasing demands of numerous Internet-of-Things mobile devices (IMDs). To address the complex interferences caused by small base stations (SBSs
Externí odkaz:
http://arxiv.org/abs/2410.14142
To enhance resource utilization and address interference issues in ultra-dense networks with mobile edge computing (MEC), a resource utilization approach is first introduced, which integrates orthogonal frequency division multiple access (OFDMA) and
Externí odkaz:
http://arxiv.org/abs/2410.12186
Despite their success, large language models (LLMs) face the critical challenge of hallucinations, generating plausible but incorrect content. While much research has focused on hallucinations in multiple modalities including images and natural langu
Externí odkaz:
http://arxiv.org/abs/2410.09997
Autor:
Wu, Yunzhuo, Wu, Tong, Chen, Haoran, Cui, Yongwei, Xu, Hongyue, Jiang, Nan, Cheng, Zhen, Wu, Yizheng
Enabling field-free current-induced switching of perpendicular magnetization is essential for advancing spin-orbit-torque magnetic random access memory technology. Our research on the Pt/Co/Ru/RuO2(101) system has successfully demonstrated field-free
Externí odkaz:
http://arxiv.org/abs/2410.07946
Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These requiremen
Externí odkaz:
http://arxiv.org/abs/2410.03187
Autor:
Wu, Yi, Xiong, Zikang, Hu, Yiran, Iyengar, Shreyash S., Jiang, Nan, Bera, Aniket, Tan, Lin, Jagannathan, Suresh
Despite significant advancements in large language models (LLMs) that enhance robot agents' understanding and execution of natural language (NL) commands, ensuring the agents adhere to user-specified constraints remains challenging, particularly for
Externí odkaz:
http://arxiv.org/abs/2409.19471