1 citations · 3 across the 10 of their papers we have counts for
10 papers
Game2World Engine: Unlocking In-the-Wild Gameplay Videos for World Model Training
Wenxuan Shen, Dongna Jin, Dongping Chen
Video games provide a scalable source of training data for video world models, offering diverse environments, complex interactions, and abundant in-the-wild gameplay videos. Howeve…
Sandboxed Coding Agents are Competitive Omni-modal Task Solvers
Dongping Chen, Xuanao Huang, Zhihan Hu +3
As multimodal LLMs increasingly target video and audio, it is often assumed that such tasks require native omnimodal models. We show that this is not always the case: coding agents…
Quantifying the Gap between Understanding and Generation within Unified Multimodal Models
Chenlong Wang, Yuhang Chen, Zhihan Hu +4
Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whether these two capabilities are gen…
Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models
Rong Zhou, Dongping Chen, Zihan Jia +24
Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration o…
Reinforced Visual Perception with Tools
Zetong Zhou, Dongping Chen, Zixian Ma +6
Visual reasoning, a cornerstone of human intelligence, encompasses complex perceptual and logical processes essential for solving diverse visual problems. While advances in compute…
Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency
Chenlong Wang, Yuanning Feng, Dongping Chen +3
Recent advances in large reasoning models have enabled complex, step-by-step reasoning but often introduce significant overthinking, resulting in verbose and redundant outputs that…
Optimizing Length Compression in Large Reasoning Models
Zhengxiang Cheng, Dongping Chen, Mingyang Fu +1
Large Reasoning Models (LRMs) have achieved remarkable success, yet they often suffer from producing unnecessary and verbose reasoning chains. We identify a core aspect of this iss…
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
Peter Sushko, Ayana Bharadwaj, Zhi Yang Lim +6
Existing image editing models struggle to meet real-world demands. Despite excelling in academic benchmarks, they have yet to be widely adopted for real user needs. Datasets that p…
Perception Tokens Enhance Visual Reasoning in Multimodal Language Models
Mahtab Bigverdi, Zelun Luo, Cheng-Yu Hsieh +4
Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit…