211 citations · 822 across the 80 of their papers we have counts for
72 papers · 1 filter
Rubrics as Visual-Repair Context for Self-Evolving UI-to-Code Generation
Tianyi Xiong, Zhengyuan Yang, Xiaofei Wang +10
Large vision-language models have shown strong progress in UI-to-code generation, yet their test-time self-evolution remains unstable. We first identify a fundamental obstacle, ter…
Efficient Frame Selection for Long Videos at Test Time with Attention-Based MLLM Selectors
Yilin Wang, Xiangxi Zheng, Dongxing Mao +6
Understanding long videos with multimodal large language models (MLLMs) requires selecting a compact set of frames from thousands of candidates, yet identifying the right frames se…
3D-CoS: A New 3D Reconstruction Paradigm Based on VLM Code Synthesis
Yuhao Wang, Puyi Wang, Linjie Li +3
Most recent 3D reconstruction and editing systems operate on implicit and explicit representations such as NeRF, point clouds, or meshes. While these representations enable high-fi…
Residual Decoder Adapter: ID-Preserving Tokenizer Adaption for Autoregressive Text Rendering
Dongxing Mao, Jinpeng Wang, Jiahao Tang +6
Visual Autoregressive (AR) models generate images by predicting discrete tokens that are decoded by a visual tokenizer. Despite demonstrating strong overall image generation abilit…
TextGround4M: A Prompt-Aligned Dataset for Layout-Aware Text Rendering
Dongxing Mao, Yilin Wang, Linjie Li +2
Despite recent advances in text-to-image generation, models still struggle to accurately render prompt-specified text with correct spatial layout -- especially in multi-span, struc…
FlowInOne:Unifying Multimodal Generation as Image-in, Image-out Flow Matching
Junchao Yi, Rui Zhao, Jiahao Tang +7
Multimodal generation has long been dominated by text-driven pipelines where language dictates vision but cannot reason or create within it. We challenge this paradigm by asking wh…
Glance: Accelerating Diffusion Models with 1 Sample
Zhuobai Dong, Rui Zhao, Songjie Wu +5
Diffusion models have achieved remarkable success in image generation, yet their deployment remains constrained by the heavy computational cost and the need for numerous inference…
TechImage-Bench: Rubric-Based Evaluation for Technical Image Generation
Minheng Ni, Zhengyuan Yang, Yaowen Zhang +9
We study technical image generation, where a model must synthesize information-dense, scientifically precise illustrations from detailed descriptions rather than merely produce vis…
Computer-Use Agents as Judges for Generative User Interface
Kevin Qinghong Lin, Siyuan Hu, Linjie Li +4
Computer-Use Agents (CUA) are becoming increasingly capable of autonomously operating digital environments through Graphical User Interfaces (GUI). Yet, most GUI remain designed pr…
Exploring a Unified Vision-Centric Contrastive Alternatives on Multi-Modal Web Documents
Yiqi Lin, Alex Jinpeng Wang, Linjie Li +2
Contrastive vision-language models such as CLIP have demonstrated strong performance across a wide range of multimodal tasks by learning from aligned image-text pairs. However, the…
EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing
Tianyu Chen, Yasi Zhang, Zhi Zhang +13
Instruction-based image editing has advanced rapidly, yet reliable and interpretable evaluation remains a bottleneck. Current protocols either (i) depend on paired reference images…
GLIMPSE: Do Large Vision-Language Models Truly Think With Videos or Just Glimpse at Them?
Yiyang Zhou, Linjie Li, Shi Qiu +10
Existing video benchmarks often resemble image-based benchmarks, with question types like "What actions does the person perform throughout the video?" or "What color is the woman's…
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Zhaochen Su, Peng Xia, Hangyu Guo +12
Recent progress in multimodal reasoning has been significantly advanced by textual Chain-of-Thought (CoT), a paradigm where models conduct reasoning within language. This text-cent…
ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs
Xiyao Wang, Zhengyuan Yang, Chao Feng +10
Reinforcement learning (RL) has shown great effectiveness for fine-tuning large language models (LLMs) using tasks that are challenging yet easily verifiable, such as math reasonin…
SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
Xiyao Wang, Zhengyuan Yang, Chao Feng +6
We introduce ThinkLite-VL, a family of visual reasoning models that achieve state-of-the-art (SoTA) performance using an order of magnitude fewer training samples, relying purely o…
Point-RFT: Improving Multimodal Reasoning with Visually Grounded Reinforcement Finetuning
Minheng Ni, Zhengyuan Yang, Linjie Li +4
Recent advances in large language models have significantly improved textual reasoning through the effective use of Chain-of-Thought (CoT) and reinforcement learning. However, exte…
Cross-Task Generalization Between Understanding and Generation in Unified Vision-Language Models: A Controlled Study
Jihai Zhang, Tianle Li, Linjie Li +2
Unified vision-language models (VLMs) aim to support both visual understanding and generation within a single framework, but it remains unclear when mixed training benefits both ca…
OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning
Zhaochen Su, Linjie Li, Mingyang Song +8
While humans can flexibly leverage interactive visual cognition for complex problem-solving, enabling Large Vision-Language Models (LVLMs) to learn similarly adaptive behaviors wit…
V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models
Xiangxi Zheng, Linjie Li, Zhengyuan Yang +5
Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existing static image-text benchmarks…
Zero-Shot Audio-Visual Editing via Cross-Modal Delta Denoising
Yan-Bo Lin, Kevin Lin, Zhengyuan Yang +6
In this paper, we introduce zero-shot audio-video editing, a novel task that requires transforming original audio-visual content to align with a specified textual prompt without ad…
Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models
Alex Jinpeng Wang, Linjie Li, Zhengyuan Yang +2
Recent advancements in autoregressive and diffusion models have led to strong performance in image generation with short scene text words. However, generating coherent, long-form t…
ImageGen-CoT: Enhancing Text-to-Image In-context Learning with Chain-of-Thought Reasoning
Jiaqi Liao, Zhengyuan Yang, Linjie Li +4
In this work, we study the problem of Text-to-Image In-Context Learning (T2I-ICL). While Unified Multimodal LLMs (MLLMs) have advanced rapidly in recent years, they struggle with c…
TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation
Alex Jinpeng Wang, Dongxing Mao, Jiawei Zhang +9
Text-conditioned image generation has gained significant attention in recent years and are processing increasingly longer and comprehensive text prompt. In everyday life, dense and…
Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark
Yunzhuo Hao, Jiawei Gu, Huichen Will Wang +4
The ability to organically reason over and with both text and images is a pillar of human intelligence, yet the ability of Multimodal Large Language Models (MLLMs) to perform such…