13 citations · 65 across the 26 of their papers we have counts for
32 papers
OpticalRec: Unified Optical Vision-Language Representation for Multimodal Recommendation
Yueqi Wang, Zitian Guo, Yupeng Hou +9
Recent advances in vision-language modeling have substantially improved multimodal encoding, retrieval and reasoning. Yet for multimodal recommendation, encoding rich item vision-l…
GLEAM: Learning to Match and Explain in Cross-View Geo-Localization
Xudong Lu, Zhi Zheng, Yi Wan +11
Cross-View Geo-Localization (CVGL) focuses on identifying correspondences between images captured from distinct perspectives of the same geographical location. However, existing CV…
Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling
Yi Xin, Juncheng Yan, Qi Qin +18
We present Lumina-mGPT 2.0, a stand-alone, decoder-only autoregressive model that revisits and revitalizes the autoregressive paradigm for high-quality image generation and beyond.…
T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
Dongzhi Jiang, Ziyu Guo, Renrui Zhang +6
Recent advancements in large language models have demonstrated how chain-of-thought (CoT) and reinforcement learning (RL) can improve performance. However, applying such reasoning…
Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPO
Chengzhuo Tong, Ziyu Guo, Renrui Zhang +5
Recent advancements underscore the significant role of Reinforcement Learning (RL) in enhancing the Chain-of-Thought (CoT) reasoning capabilities of large language models (LLMs). T…
MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs
Jiakang Yuan, Tianshuo Peng, Yilei Jiang +8
Logical reasoning is a fundamental aspect of human intelligence and an essential capability for multimodal large language models (MLLMs). Despite the significant advancement in mul…
From Reflection to Perfection: Scaling Inference-Time Optimization for Text-to-Image Diffusion Models via Reflection Tuning
Le Zhuo, Liangbing Zhao, Sayak Paul +6
Recent text-to-image diffusion models achieve impressive visual quality through extensive scaling of training data and model parameters, yet they often struggle with complex scenes…
TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
Daocheng Fu, Jianlong Chen, Renqiu Xia +12
Geometric problem solving (GPS) requires precise multimodal understanding and rigorous, step-by-step logical reasoning. However, developing capable Multimodal Large Language Models…
3DAxisPrompt: Promoting the 3D Grounding and Reasoning in GPT-4o
Dingning Liu, Cheng Wang, Peng Gao +4
Multimodal Large Language Models (MLLMs) exhibit impressive capabilities across a variety of tasks, especially when equipped with carefully designed visual prompts. However, existi…
PiSA: A Self-Augmented Data Engine and Training Strategy for 3D Understanding with Large Models
Zilu Guo, Hongbin Lin, Zhihao Yuan +6
3D Multimodal Large Language Models (MLLMs) have recently made substantial advancements. However, their potential remains untapped, primarily due to the limited quantity and subopt…
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Dongzhi Jiang, Renrui Zhang, Ziyu Guo +11
Answering questions with Chain-of-Thought (CoT) has significantly enhanced the reasoning capabilities of Large Language Models (LLMs), yet its impact on Large Multimodal Models (LM…
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models
Jiayi Lei, Renrui Zhang, Xiangfei Hu +12
With the rapid development of diffusion models, text-to-image(T2I) models have made significant progress, showcasing impressive abilities in prompt following and image generation.…
Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step
Ziyu Guo, Renrui Zhang, Chengzhuo Tong +9
Chain-of-Thought (CoT) reasoning has been extensively explored in large models to tackle complex understanding tasks. However, it still remains an open question whether such strate…
TAR3D: Creating High-Quality 3D Assets via Next-Part Prediction
Xuying Zhang, Yutong Liu, Yangguang Li +8
We present TAR3D, a novel framework that consists of a 3D-aware Vector Quantized-Variational AutoEncoder (VQ-VAE) and a Generative Pre-trained Transformer (GPT) to generate high-qu…
Chimera: Improving Generalist Model with Domain-Specific Experts
Tianshuo Peng, Mingsheng Li, Jiakang Yuan +11
Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks.…
CoPESD: A Multi-Level Surgical Motion Dataset for Training Large Vision-Language Models to Co-Pilot Endoscopic Submucosal Dissection
Guankun Wang, Han Xiao, Huxin Gao +6
submucosal dissection (ESD) enables rapid resection of large lesions, minimizing recurrence rates and improving long-term overall survival. Despite these advantages, ESD is technic…
Unleashing the Potentials of Likelihood Composition for Multi-modal Language Models
Shitian Zhao, Renrui Zhang, Xu Luo +3
Model fusing has always been an important topic, especially in an era where large language models (LLM) and multi-modal language models (MLM) with different architectures, paramete…
PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
Weifeng Lin, Xinyu Wei, Renrui Zhang +8
This paper presents a versatile image-to-image visual assistant, PixWizard, designed for image generation, manipulation, and translation based on free-from language instructions. T…
MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines
Dongzhi Jiang, Renrui Zhang, Ziyu Guo +11
The advent of Large Language Models (LLMs) has paved the way for AI search engines, e.g., SearchGPT, showcasing a new paradigm in human-internet interaction. However, most current…
SAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners
Ziyu Guo, Renrui Zhang, Xiangyang Zhu +4
We introduce SAM2Point, a preliminary exploration adapting Segment Anything Model 2 (SAM 2) for zero-shot and promptable 3D segmentation. SAM2Point interprets any 3D data as a seri…
MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
Renrui Zhang, Xinyu Wei, Dongzhi Jiang +11
The mathematical capabilities of Multi-modal Large Language Models (MLLMs) remain under-explored with three areas to be improved: visual encoding of math diagrams, diagram-language…
Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers
Peng Gao, Le Zhuo, Dongyang Liu +17
Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lac…
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
Xudong Lu, Aojun Zhou, Yuhui Xu +3
Large Language Models (LLMs) have become pivotal in advancing the field of artificial intelligence, yet their immense sizes pose significant challenges for both fine-tuning and dep…
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo +18
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus rem…