77 citations · 154 across the 7 of their papers we have counts for
7 papers
CogVLM2: Visual Language Models for Image and Video Understanding
Wenyi Hong, Weihan Wang, Ming Ding +22
Beginning with VisualGLM and CogVLM, we are continuously exploring VLMs in pursuit of enhanced vision-language fusion, efficient higher-resolution architecture, and broader modalit…
CogCoM: A Visual Language Model with Chain-of-Manipulations Reasoning
Ji Qi, Ming Ding, Weihan Wang +8
Vision-Language Models (VLMs) have demonstrated their broad effectiveness thanks to extensive training in aligning visual instructions to responses. However, such training of concl…
CogAgent: A Visual Language Model for GUI Agents
Wenyi Hong, Weihan Wang, Qingsong Lv +11
People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e.g., computer or smartphone screens. Large language models (LLMs) such…
CogVLM: Visual Expert for Pretrained Language Models
Weihan Wang, Qingsong Lv, Wenmeng Yu +13
We introduce CogVLM, a powerful open-source visual language foundation model. Different from the popular shallow alignment method which maps image features into the input space of…
GPT Can Solve Mathematical Problems Without a Calculator
Zhen Yang, Ming Ding, Qingsong Lv +5
Previous studies have typically assumed that large language models are unable to accurately perform arithmetic operations, particularly multiplication of >8 digits, and operations…
Parameter-Efficient Tuning Makes a Good Classification Head
Zhuoyi Yang, Ming Ding, Yanhui Guo +2
In recent years, pretrained models revolutionized the paradigm of natural language understanding (NLU), where we append a randomly initialized classification head after the pretrai…
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks
Qingsong Lv, Ming Ding, Qiang Liu +7
Heterogeneous graph neural networks (HGNNs) have been blossoming in recent years, but the unique data processing and evaluation setups used by each work obstruct a full understandi…