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20222024
most citedChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

180 citations · 196 across the 3 of their papers we have counts for

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cs.CL2024180 cited

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Team GLM, :, Aohan Zeng +56

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…

cs.CL2023

AlignBench: Benchmarking Chinese Alignment of Large Language Models

Xiao Liu, Xuanyu Lei, Shengyuan Wang +15

Alignment has become a critical step for instruction-tuned Large Language Models (LLMs) to become helpful assistants. However, the effective evaluation of alignment for emerging Ch…

cs.CL2023

Black-Box Prompt Optimization: Aligning Large Language Models without Model Training

Jiale Cheng, Xiao Liu, Kehan Zheng +5

Large language models (LLMs) have shown impressive success in various applications. However, these models are often not well aligned with human intents, which calls for additional…

cs.CL202316 cited

Safety Assessment of Chinese Large Language Models

Hao Sun, Zhexin Zhang, Jiawen Deng +2

With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting an…

cs.CL2022

Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation

Zhexin Zhang, Jiale Cheng, Hao Sun +5

Large pretrained language models can easily produce toxic or biased content, which is prohibitive for practical use. In order to detect such toxic generations, existing methods rel…