Zobrazeno 1 - 10
of 170 510
pro vyhledávání: '"Shuo, An"'
Reinforcement learning (RL) algorithms can be divided into two classes: model-free algorithms, which are sample-inefficient, and model-based algorithms, which suffer from model bias. Dyna-style algorithms combine these two approaches by using simulat
Externí odkaz:
http://arxiv.org/abs/2410.12160
Autor:
Tian, Runchu, Li, Yanghao, Fu, Yuepeng, Deng, Siyang, Luo, Qinyu, Qian, Cheng, Wang, Shuo, Cong, Xin, Zhang, Zhong, Wu, Yesai, Lin, Yankai, Wang, Huadong, Liu, Xiaojiang
Positional bias in large language models (LLMs) hinders their ability to effectively process long inputs. A prominent example is the "lost in the middle" phenomenon, where LLMs struggle to utilize relevant information situated in the middle of the in
Externí odkaz:
http://arxiv.org/abs/2410.14641
Autor:
Tang, Shuo, Pang, Xianghe, Liu, Zexi, Tang, Bohan, Ye, Rui, Dong, Xiaowen, Wang, Yanfeng, Chen, Siheng
Post-training is essential for enabling large language models (LLMs) to follow human instructions. Inspired by the recent success of using LLMs to simulate human society, we leverage multi-agent simulation to automatically generate diverse text-based
Externí odkaz:
http://arxiv.org/abs/2410.14251
Diffusion models (DMs) have been successfully applied to real image editing. These models typically invert images into latent noise vectors used to reconstruct the original images (known as inversion), and then edit them during the inference process.
Externí odkaz:
http://arxiv.org/abs/2410.14247
This paper focuses on the development of an advanced intelligent article scoring system that not only assesses the overall quality of written work but also offers detailed feature-based scoring tailored to various article genres. By integrating the p
Externí odkaz:
http://arxiv.org/abs/2410.14165
Autor:
Huang, Jiatan, Li, Mingchen, Yao, Zonghai, Yang, Zhichao, Xiao, Yongkang, Ouyang, Feiyun, Li, Xiaohan, Han, Shuo, Yu, Hong
Answering complex real-world questions often requires accurate retrieval from textual knowledge graphs (TKGs). The scarcity of annotated data, along with intricate topological structures, makes this task particularly challenging. As the nature of rel
Externí odkaz:
http://arxiv.org/abs/2410.13987
Elastic light-by-light (LbL) scattering, one of the most fascinating processes in the Standard Model (SM), has recently been observed in the ultraperipheral collisions (UPCs) of relativistic heavy ions in the Atlas and CMS experiments at the Large Ha
Externí odkaz:
http://arxiv.org/abs/2410.13781
Autor:
Guo, Yuchen, Yang, Shuo
Recent studies have unveiled new possibilities for discovering intrinsic quantum phases that are unique to open systems, including phases with average symmetry-protected topological (ASPT) order and strong-to-weak spontaneous symmetry breaking (SWSSB
Externí odkaz:
http://arxiv.org/abs/2410.13734
Autor:
Li, Xinze, Mei, Sen, Liu, Zhenghao, Yan, Yukun, Wang, Shuo, Yu, Shi, Zeng, Zheni, Chen, Hao, Yu, Ge, Liu, Zhiyuan, Sun, Maosong, Xiong, Chenyan
Retrieval-Augmented Generation (RAG) has proven its effectiveness in mitigating hallucinations in Large Language Models (LLMs) by retrieving knowledge from external resources. To adapt LLMs for RAG pipelines, current approaches use instruction tuning
Externí odkaz:
http://arxiv.org/abs/2410.13509
Recommender systems predict personalized item rankings based on user preference distributions derived from historical behavior data. Recently, diffusion models (DMs) have gained attention in recommendation for their ability to model complex distribut
Externí odkaz:
http://arxiv.org/abs/2410.13117