Zobrazeno 1 - 10
of 492
pro vyhledávání: '"Ye Junjie"'
Autor:
Ye, Junjie, Yang, Yuming, Zhang, Qi, Gui, Tao, Huang, Xuanjing, Wang, Peng, Shi, Zhongchao, Fan, Jianping
Large language models (LLMs) encode extensive world knowledge through pre-training on massive datasets, which can then be fine-tuned for the question-answering (QA) task. However, effective strategies for fine-tuning LLMs for the QA task remain large
Externí odkaz:
http://arxiv.org/abs/2409.15825
Autor:
Zhang, Ming, Huang, Caishuang, Wu, Yilong, Liu, Shichun, Zheng, Huiyuan, Dong, Yurui, Shen, Yujiong, Dou, Shihan, Zhao, Jun, Ye, Junjie, Zhang, Qi, Gui, Tao, Huang, Xuanjing
Task-oriented dialogue (TOD) systems aim to efficiently handle task-oriented conversations, including information collection. How to utilize TOD accurately, efficiently and effectively for information collection has always been a critical and challen
Externí odkaz:
http://arxiv.org/abs/2407.21693
Autor:
Kuang, Yuxuan, Ye, Junjie, Geng, Haoran, Mao, Jiageng, Deng, Congyue, Guibas, Leonidas, Wang, He, Wang, Yue
This work proposes a retrieve-and-transfer framework for zero-shot robotic manipulation, dubbed RAM, featuring generalizability across various objects, environments, and embodiments. Unlike existing approaches that learn manipulation from expensive i
Externí odkaz:
http://arxiv.org/abs/2407.04689
Autor:
Huang, Caishuang, Zhao, Wanxu, Zheng, Rui, Lv, Huijie, Dou, Shihan, Li, Sixian, Wang, Xiao, Zhou, Enyu, Ye, Junjie, Yang, Yuming, Gui, Tao, Zhang, Qi, Huang, Xuanjing
As the development of large language models (LLMs) rapidly advances, securing these models effectively without compromising their utility has become a pivotal area of research. However, current defense strategies against jailbreak attacks (i.e., effo
Externí odkaz:
http://arxiv.org/abs/2406.18118
Autor:
Yang, Yuming, Zhao, Wantong, Huang, Caishuang, Ye, Junjie, Wang, Xiao, Zheng, Huiyuan, Nan, Yang, Wang, Yuran, Xu, Xueying, Huang, Kaixin, Zhang, Yunke, Gui, Tao, Zhang, Qi, Huang, Xuanjing
Open Named Entity Recognition (NER), which involves identifying arbitrary types of entities from arbitrary domains, remains challenging for Large Language Models (LLMs). Recent studies suggest that fine-tuning LLMs on extensive NER data can boost the
Externí odkaz:
http://arxiv.org/abs/2406.11192
Autor:
Dou, Shihan, Liu, Yan, Zhou, Enyu, Li, Tianlong, Jia, Haoxiang, Xiong, Limao, Zhao, Xin, Ye, Junjie, Zheng, Rui, Gui, Tao, Zhang, Qi, Huang, Xuanjing
The success of Reinforcement Learning from Human Feedback (RLHF) in language model alignment is critically dependent on the capability of the reward model (RM). However, as the training process progresses, the output distribution of the policy model
Externí odkaz:
http://arxiv.org/abs/2405.00438
It is critical to design efficient beamforming in reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) systems for enhancing spectrum utilization. However, conventional methods often have limitations, either incu
Externí odkaz:
http://arxiv.org/abs/2403.17324
Autor:
Zhong, Ruizhe, Ye, Junjie, Tang, Zhentao, Kai, Shixiong, Yuan, Mingxuan, Hao, Jianye, Yan, Junchi
Pre-routing timing prediction has been recently studied for evaluating the quality of a candidate cell placement in chip design. It involves directly estimating the timing metrics for both pin-level (slack, slew) and edge-level (net delay, cell delay
Externí odkaz:
http://arxiv.org/abs/2403.00012
Autor:
Lv, Huijie, Wang, Xiao, Zhang, Yuansen, Huang, Caishuang, Dou, Shihan, Ye, Junjie, Gui, Tao, Zhang, Qi, Huang, Xuanjing
Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs). This paper delves into the mechanisms behind such successful attacks, int
Externí odkaz:
http://arxiv.org/abs/2402.16717
Despite the impressive capabilities of large language models (LLMs), their performance on information extraction tasks is still not entirely satisfactory. However, their remarkable rewriting capabilities and extensive world knowledge offer valuable i
Externí odkaz:
http://arxiv.org/abs/2402.14568