4 citations · 7 across the 9 of their papers we have counts for
15 papers
AudioLift: Audio-Driven Single Image to Full-Head Gaussian Avatar via Multi-view Video Generation
Zhuoyuan Jiang, Weijie Lyu, Xiaoyuan Wang +2
Existing 3D talking avatar methods mainly rely on parametric face models including 3DMM or FLAME, whose compact motion representations limit their ability to synthesize extreme exp…
Dual Exam: Controlled Evaluation of Multimodal Agents and World Models
Zhefan Rao, Meng Chu, Xuan Zhang +80
World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction require…
COMPASS: Contextual Moment Prior Alignment for Generalizable AIGI Detection
Zhan Yang, Tiancheng Shen, Weijie Lyu +4
Generalizable AI-generated image (AIGI) and deepfake detection remain challenging due to the asymmetry phenomenon, where adaptation to limited training distributions can degrade th…
QK-Edit: Revisiting Attention-based Injection in MM-DiT for Image and Video Editing
Tiancheng Shen, Zilong Huang, Xiangtai Li +6
Multimodal Diffusion Transformers (MM-DiTs) have recently emerged as a powerful framework for unified text-vision synthesis, surpassing traditional U-Net architectures in generativ…
Getting Space Right: Agentic Rewards for Image Generation
Xiaofeng Tan, Jiaxin Lin, Haobo Yuan +5
Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accurate rewards and effective onl…
LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning
Bang Xiao, Wenqi Jia, Ozgur Kara +5
Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as that of another entity or an…
Dual-Grained Agent Memory and Shapley Context Attribution for Multimodal Agentic Learner
Jieke Wang, Tiancheng Shen, Yibo Yang +1
Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-level adaptation is unavailable…
Bridging Physical Reasoning and Task Generalization via Visual Action Outcome Reasoning Alignment
Han-Jun Ko, Jr-Jen Chen, Haobo Yuan +4
Vision-language models (VLMs) struggle to generalize in interactive physical reasoning, particularly under unseen tasks and environments. Two key failure modes are prominent: hallu…
H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions
Shiping Zhu, Yibo Yang, Zhengyang Wang +3
Large language model agents are increasingly deployed in human-human interaction settings, such as meeting assistants and clinical documentation systems, where they must observe co…
ParaCook: On Time-Efficient Planning for Multi-Agent Systems
Shiqi Zhang, Xinbei Ma, Yunqing Xu +7
Large Language Models (LLMs) exhibit strong reasoning abilities for planning long-horizon, real-world tasks, yet existing agent benchmarks focus on task completion while neglecting…
Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence
Yibo Yang, Sihao Liu, Chuan Rao +5
Conventional low-rank adaptation methods build adapters without considering data context, leading to sub-optimal fine-tuning performance and severe forgetting of inherent world kno…
Optimizing Singular Spectrum for Large Language Model Compression
Dengjie Li, Tiancheng Shen, Yao Zhou +7
Large language models (LLMs) have demonstrated remarkable capabilities, yet prohibitive parameter complexity often hinders their deployment. Existing singular value decomposition (…
Empowering Visual Creativity: A Vision-Language Assistant to Image Editing Recommendations
Tiancheng Shen, Jun Hao Liew, Long Mai +3
Advances in text-based image generation and editing have revolutionized content creation, enabling users to create impressive content from imaginative text prompts. However, existi…
High-Quality Entity Segmentation and Grounding
Lu Qi, Yi-Wen Chen, Tao Zhang +4
In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg co…
Rethinking Evaluation Metrics of Open-Vocabulary Segmentaion
Hao Zhou, Tiancheng Shen, Xu Yang +4
In this paper, we highlight a problem of evaluation metrics adopted in the open-vocabulary segmentation. That is, the evaluation process still heavily relies on closed-set metrics…