77 citations · 128 across the 20 of their papers we have counts for
12 papers · 1 filter
VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation
Jiazheng Xu, Yu Huang, Jiale Cheng +19
Visual generative models have achieved remarkable progress in synthesizing photorealistic images and videos, yet aligning their outputs with human preferences across critical dimen…
DreamPolish: Domain Score Distillation With Progressive Geometry Generation
Yean Cheng, Ziqi Cai, Ming Ding +5
We introduce DreamPolish, a text-to-3D generation model that excels in producing refined geometry and high-quality textures. In the geometry construction phase, our approach levera…
VisScience: An Extensive Benchmark for Evaluating K12 Educational Multi-modal Scientific Reasoning
Zhihuan Jiang, Zhen Yang, Jinhao Chen +4
Multi-modal large language models (MLLMs) have demonstrated promising capabilities across various tasks by integrating textual and visual information to achieve visual understandin…
MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model
Zhen Yang, Jinhao Chen, Zhengxiao Du +6
Large language models (LLMs) have demonstrated significant capabilities in mathematical reasoning, particularly with text-based mathematical problems. However, current multi-modal…
VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents
Xiao Liu, Tianjie Zhang, Yu Gu +27
Large Multimodal Models (LMMs) have ushered in a new era in artificial intelligence, merging capabilities in both language and vision to form highly capable Visual Foundation Agent…
CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Zhuoyi Yang, Jiayan Teng, Wendi Zheng +15
We present CogVideoX, a large-scale text-to-video generation model based on diffusion transformer, which can generate 10-second continuous videos aligned with text prompt, with a f…
LVBench: An Extreme Long Video Understanding Benchmark
Weihan Wang, Zehai He, Wenyi Hong +9
Recent progress in multimodal large language models has markedly enhanced the understanding of short videos (typically under one minute), and several evaluation datasets have emerg…
Inf-DiT: Upsampling Any-Resolution Image with Memory-Efficient Diffusion Transformer
Zhuoyi Yang, Heyang Jiang, Wenyi Hong +5
Diffusion models have shown remarkable performance in image generation in recent years. However, due to a quadratic increase in memory during generating ultra-high-resolution image…
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…
TriSampler: A Better Negative Sampling Principle for Dense Retrieval
Zhen Yang, Zhou Shao, Yuxiao Dong +1
Negative sampling stands as a pivotal technique in dense retrieval, essential for training effective retrieval models and significantly impacting retrieval performance. While exist…
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…