Zobrazeno 1 - 10
of 8 376
pro vyhledávání: '"Zhu,Chen"'
Autor:
He, Yun, Jin, Di, Wang, Chaoqi, Bi, Chloe, Mandyam, Karishma, Zhang, Hejia, Zhu, Chen, Li, Ning, Xu, Tengyu, Lv, Hongjiang, Bhosale, Shruti, Zhu, Chenguang, Sankararaman, Karthik Abinav, Helenowski, Eryk, Kambadur, Melanie, Tayade, Aditya, Ma, Hao, Fang, Han, Wang, Sinong
Large Language Models (LLMs) have demonstrated impressive capabilities in various tasks, including instruction following, which is crucial for aligning model outputs with user expectations. However, evaluating LLMs' ability to follow instructions rem
Externí odkaz:
http://arxiv.org/abs/2410.15553
Autor:
Wang, Chaoqi, Zhao, Zhuokai, Zhu, Chen, Sankararaman, Karthik Abinav, Valko, Michal, Cao, Xuefei, Chen, Zhaorun, Khabsa, Madian, Chen, Yuxin, Ma, Hao, Wang, Sinong
Recent advancements in generative models, particularly large language models (LLMs) and diffusion models, have been driven by extensive pretraining on large datasets followed by post-training. However, current post-training methods such as reinforcem
Externí odkaz:
http://arxiv.org/abs/2410.12138
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the significant challenge of quickly and accurately pinpointing positions that align with their skills and prefere
Externí odkaz:
http://arxiv.org/abs/2410.07671
Parking challenges escalate significantly during large events such as concerts and sports games, yet few studies address dynamic parking lot assignments in these occasions. This paper introduces a smart navigation system designed to optimize parking
Externí odkaz:
http://arxiv.org/abs/2410.18983
Autor:
Xu, Tengyu, Helenowski, Eryk, Sankararaman, Karthik Abinav, Jin, Di, Peng, Kaiyan, Han, Eric, Nie, Shaoliang, Zhu, Chen, Zhang, Hejia, Zhou, Wenxuan, Zeng, Zhouhao, He, Yun, Mandyam, Karishma, Talabzadeh, Arya, Khabsa, Madian, Cohen, Gabriel, Tian, Yuandong, Ma, Hao, Wang, Sinong, Fang, Han
Reinforcement learning from human feedback (RLHF) has become the leading approach for fine-tuning large language models (LLM). However, RLHF has limitations in multi-task learning (MTL) due to challenges of reward hacking and extreme multi-objective
Externí odkaz:
http://arxiv.org/abs/2409.20370
Visual geo-localization demands in-depth knowledge and advanced reasoning skills to associate images with precise real-world geographic locations. Existing image database retrieval methods are limited by the impracticality of storing sufficient visua
Externí odkaz:
http://arxiv.org/abs/2408.11312
In this paper, we present the technical details and periodic findings of our project, CareerAgent, which aims to build a generative simulation framework for a Holacracy organization using Large Language Model-based Autonomous Agents. Specifically, th
Externí odkaz:
http://arxiv.org/abs/2408.11826
Factor analysis, often regarded as a Bayesian variant of matrix factorization, offers superior capabilities in capturing uncertainty, modeling complex dependencies, and ensuring robustness. As the deep learning era arrives, factor analysis is receivi
Externí odkaz:
http://arxiv.org/abs/2407.21740
Autor:
Liang, Siyun, Zhao, Zhouxiang, Zhu, Chen, Yang, Zhaohui, Yang, Yinchao, Shikh-Bahaei, Mohammad, Zhang, Zhaoyang
In this paper, the problem of minimum rate maximization for probabilistic semantic communication (PSCom) in industrial Internet of Things (IIoT) is investigated. In the considered model, users employ semantic information extraction techniques to comp
Externí odkaz:
http://arxiv.org/abs/2407.02922
Many studies have revealed that large language models (LLMs) exhibit uneven awareness of different contextual positions. Their limited context awareness can lead to overlooking critical information and subsequent task failures. While several approach
Externí odkaz:
http://arxiv.org/abs/2406.19598