19 citations · 45 across the 12 of their papers we have counts for
8 papers
MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks
Xiaocui Yang, Wenfang Wu, Shi Feng +7
The popularity of multimodal large language models (MLLMs) has triggered a recent surge in research efforts dedicated to evaluating these models. Nevertheless, existing evaluation…
Controllable Data Generation Via Iterative Data-Property Mutual Mappings
Bo Pan, Muran Qin, Shiyu Wang +2
Deep generative models have been widely used for their ability to generate realistic data samples in various areas, such as images, molecules, text, and speech. One major goal of d…
Cones 2: Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu, Yifei Zhang, Yujun Shen +7
Synthesizing images with user-specified subjects has received growing attention due to its practical applications. Despite the recent success in single subject customization, exist…
Cones: Concept Neurons in Diffusion Models for Customized Generation
Zhiheng Liu, Ruili Feng, Kai Zhu +6
Human brains respond to semantic features of presented stimuli with different neurons. It is then curious whether modern deep neural networks admit a similar behavior pattern. Spec…
Beyond Instance Discrimination: Relation-aware Contrastive Self-supervised Learning
Yifei Zhang, Chang Liu, Yu Zhou +3
Contrastive self-supervised learning (CSL) based on instance discrimination typically attracts positive samples while repelling negatives to learn representations with pre-defined…
MulZDG: Multilingual Code-Switching Framework for Zero-shot Dialogue Generation
Yongkang Liu, Shi Feng, Daling Wang +1
Building dialogue generation systems in a zero-shot scenario remains a huge challenge, since the typical zero-shot approaches in dialogue generation rely heavily on large-scale pre…