439 citations · 672 across the 22 of their papers we have counts for
22 papers
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Yifan Xu, Xiao Liu, Xinghan Liu +9
Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem-solving. While many s…
ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback
Zhenyu Hou, Yilin Niu, Zhengxiao Du +8
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 f…
Extensive Self-Contrast Enables Feedback-Free Language Model Alignment
Xiao Liu, Xixuan Song, Yuxiao Dong +1
Reinforcement learning from human feedback (RLHF) has been a central technique for recent large language model (LLM) alignment. However, its heavy dependence on costly human or LLM…
Open-World Semi-Supervised Learning for Node Classification
Yanling Wang, Jing Zhang, Lingxi Zhang +5
Open-world semi-supervised learning (Open-world SSL) for node classification, that classifies unlabeled nodes into seen classes or multiple novel classes, is a practical but under-…
CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion
Wendi Zheng, Jiayan Teng, Zhuoyi Yang +6
Recent advancements in text-to-image generative systems have been largely driven by diffusion models. However, single-stage text-to-image diffusion models still face challenges, in…
Does Negative Sampling Matter? A Review with Insights into its Theory and Applications
Zhen Yang, Ming Ding, Tinglin Huang +5
Negative sampling has swiftly risen to prominence as a focal point of research, with wide-ranging applications spanning machine learning, computer vision, natural language processi…