4 citations · 6 across the 13 of their papers we have counts for
15 papers
MergeTok: Unified Continuous and Discrete Visual Tokenization via Token Merging
Luyuan Zhang, Siyuan Li, Zedong Wang +7
Most visual tokenizers for image generation are bifurcated into two families with complementary limitations: continuous VAEs offer high-fidelity reconstruction but suffer from dens…
DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents
Kai Shi, Jun Yang, Ni Yang +6
Mobile Phone Agents (MPAs) have emerged as a promising research direction due to their broad applicability across diverse scenarios. While Multimodal Large Language Models (MLLMs)…
Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation
Yu Lei, Bingde Liu, Qingsong Xie +2
Text-to-3D generation based on score distillation of pre-trained 2D diffusion models has gained increasing interest, with variational score distillation (VSD) as a remarkable examp…
Dynamic-I2V: Exploring Image-to-Video Generation Models via Multimodal LLM
Peng Liu, Xiaoming Ren, Fengkai Liu +5
Recent advancements in image-to-video (I2V) generation have shown promising performance in conventional scenarios. However, these methods still encounter significant challenges whe…
Improved Visual-Spatial Reasoning via R1-Zero-Like Training
Zhenyi Liao, Qingsong Xie, Yanhao Zhang +4
Increasing attention has been placed on improving the reasoning capacities of multi-modal large language models (MLLMs). As the cornerstone for AI agents that function in the physi…
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization
Siyuan Li, Luyuan Zhang, Zedong Wang +8
Masked Image Modeling (MIM) with Vector Quantization (VQ) has achieved great success in both self-supervised pre-training and image generation. However, most existing methods strug…