Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Huang, Minlie"'
Autor:
Wen, Bosi, Ke, Pei, Gu, Xiaotao, Wu, Lindong, Huang, Hao, Zhou, Jinfeng, Li, Wenchuang, Hu, Binxin, Gao, Wendy, Xu, Jiaxin, Liu, Yiming, Tang, Jie, Wang, Hongning, Huang, Minlie
Instruction following is one of the fundamental capabilities of large language models (LLMs). As the ability of LLMs is constantly improving, they have been increasingly applied to deal with complex human instructions in real-world scenarios. Therefo
Externí odkaz:
http://arxiv.org/abs/2407.03978
Autor:
Zhang, Zhexin, Yang, Junxiao, Ke, Pei, Cui, Shiyao, Zheng, Chujie, Wang, Hongning, Huang, Minlie
LLMs are known to be vulnerable to jailbreak attacks, even after safety alignment. An important observation is that, while different types of jailbreak attacks can generate significantly different queries, they mostly result in similar responses that
Externí odkaz:
http://arxiv.org/abs/2407.02855
Autor:
Cheng, Jiale, Lu, Yida, Gu, Xiaotao, Ke, Pei, Liu, Xiao, Dong, Yuxiao, Wang, Hongning, Tang, Jie, Huang, Minlie
Although Large Language Models (LLMs) are becoming increasingly powerful, they still exhibit significant but subtle weaknesses, such as mistakes in instruction-following or coding tasks. As these unexpected errors could lead to severe consequences in
Externí odkaz:
http://arxiv.org/abs/2406.16714
Unsupervised multitask pre-training has been the critical method behind the recent success of language models (LMs). However, supervised multitask learning still holds significant promise, as scaling it in the post-training stage trends towards bette
Externí odkaz:
http://arxiv.org/abs/2406.14491
Autor:
GLM, Team, Zeng, Aohan, Xu, Bin, Wang, Bowen, Zhang, Chenhui, Yin, Da, Rojas, Diego, Feng, Guanyu, Zhao, Hanlin, Lai, Hanyu, Yu, Hao, Wang, Hongning, Sun, Jiadai, Zhang, Jiajie, Cheng, Jiale, Gui, Jiayi, Tang, Jie, Zhang, Jing, Li, Juanzi, Zhao, Lei, Wu, Lindong, Zhong, Lucen, Liu, Mingdao, Huang, Minlie, Zhang, Peng, Zheng, Qinkai, Lu, Rui, Duan, Shuaiqi, Zhang, Shudan, Cao, Shulin, Yang, Shuxun, Tam, Weng Lam, Zhao, Wenyi, Liu, Xiao, Xia, Xiao, Zhang, Xiaohan, Gu, Xiaotao, Lv, Xin, Liu, Xinghan, Liu, Xinyi, Yang, Xinyue, Song, Xixuan, Zhang, Xunkai, An, Yifan, Xu, Yifan, Niu, Yilin, Yang, Yuantao, Li, Yueyan, Bai, Yushi, Dong, Yuxiao, Qi, Zehan, Wang, Zhaoyu, Yang, Zhen, Du, Zhengxiao, Hou, Zhenyu, Wang, Zihan
We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes GLM-4, GLM-4-Air, and GLM-4-9B. They represent our most capable model
Externí odkaz:
http://arxiv.org/abs/2406.12793
When using language models (LMs) to solve complex problems, humans might struggle to understand the LM-generated solutions and repair the flawed ones. To assist humans in repairing them, we propose to automatically decompose complex solutions into mu
Externí odkaz:
http://arxiv.org/abs/2406.04604
Autor:
Wen, Zhihua, Tian, Zhiliang, Jian, Zexin, Huang, Zhen, Ke, Pei, Gao, Yifu, Huang, Minlie, Li, Dongsheng
Large Language Models (LLMs) are widely used for knowledge-seeking yet suffer from hallucinations. The knowledge boundary (KB) of an LLM limits its factual understanding, beyond which it may begin to hallucinate. Investigating the perception of LLMs'
Externí odkaz:
http://arxiv.org/abs/2405.14383
The open-source community is experiencing a surge in the release of large language models (LLMs) that are trained to follow instructions and align with human preference. However, further training to improve them still requires expensive computational
Externí odkaz:
http://arxiv.org/abs/2404.16792
Large language model agents have demonstrated remarkable advancements across various complex tasks. Recent works focus on optimizing the agent team or employing self-reflection to iteratively solve complex tasks. Since these agents are all based on t
Externí odkaz:
http://arxiv.org/abs/2404.05569
Autor:
Hou, Zhenyu, Niu, Yilin, Du, Zhengxiao, Zhang, Xiaohan, Liu, Xiao, Zeng, Aohan, Zheng, Qinkai, Huang, Minlie, Wang, Hongning, Tang, Jie, Dong, Yuxiao
ChatGLM is a free-to-use AI service powered by the ChatGLM family of large language models (LLMs). In this paper, we present the ChatGLM-RLHF pipeline -- a reinforcement learning from human feedback (RLHF) system -- designed to enhance ChatGLM's alig
Externí odkaz:
http://arxiv.org/abs/2404.00934