4 citations · 24 across the 56 of their papers we have counts for
61 papers
Metric-Bench: Exploring In-context Spatial Metric Reasoning in VLMs for Indoor Scenes
Yuling Xi, Haokai Zhang, Muzhi Zhu +10
Metric reasoning is a critical and challenging task for Vision Language Models (VLMs), playing a pivotal role in embodied AI tasks such as robotic manipulation and autonomous navig…
ForeDreamer: A Self-Evolving Dual-Agent Memory Architecture for Future Event Prediction
Linhao Zhong, Zongze Du, Linyu Wu +6
Open-web future event prediction requires agents to distill reliable signals from noisy, redundant, and incomplete evidence. Existing retrieval/memory mechanisms directly feed retr…
Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social Dissemination
Shuo Liang, Yixing Ma, Pengfei Zhou +33
Recent video generators can fabricate realistic depictions of wars, disasters, public emergencies, and other real-world crises, creating substantial risks of misinformation. Existi…
Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning
Zishuo Li, Bowen Yang, Changtao Miao +29
Egocentric videos of human manipulation provide scalable supervision for embodied intelligence, yet existing resources rarely combine low-cost continuous capture, manipulation-leve…
CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts
Haozhe Zhang, Sixian Li, Yifei Zhang +5
Vision-language-action (VLA) models have advanced generalist robotic manipulation, yet real-world deployment reveals a fundamental challenge: robots are equipped with diverse and h…
MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism
Cong Chen, Guo Gan, Kaixiang Ji +7
Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overco…
HORIZON: Recoverability-Governed Curriculum for Physical-Domain Scaling
Chenhao Bai, Liqin Lu, Kaijun Wang +5
Scaling robust robot policies requires more than broader randomization, because physical-domain experience must remain organized and learnable throughout training. We study when a…
Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching
Hao Zhong, Muzhi Zhu, Shenyan Zeng +8
Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making it a challenging testbed for…
MARBLE: Multi-Aspect Reward Balance for Diffusion RL
Canyu Zhao, Hao Chen, Yunze Tong +3
Reinforcement learning fine-tuning has become the dominant approach for aligning diffusion models with human preferences. However, assessing images is intrinsically a multi-dimensi…
OmniJigsaw: Enhancing Omni-Modal Reasoning via Modality-Orchestrated Reordering
Yiduo Jia, Muzhi Zhu, Hao Zhong +7
To extend the reinforcement learning post-training paradigm to omni-modal models for concurrently bolstering video-audio understanding and collaborative reasoning, we propose OmniJ…
Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration
Linhao Zhong, Linyu Wu, Wen Wang +5
Diffusion large language models (dLLMs) have recently attracted significant attention for their ability to enhance diversity, controllability, and parallelism. However, their non-s…
AGILE: Hand-Object Interaction Reconstruction from Video via Agentic Generation
Jin-Chuan Shi, Binhong Ye, Tao Liu +6
Reconstructing dynamic hand-object interactions from monocular videos is critical for dexterous manipulation data collection and creating realistic digital twins for robotics and V…
Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models
Linhao Zhong, Linyu Wu, Bozhen Fang +6
Diffusion Language Models (DLMs) offer a promising alternative for language modeling by enabling parallel decoding through iterative refinement. However, most DLMs rely on hard bin…
Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality
Zekai Luo, Zongze Du, Zhouhang Zhu +7
Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a signific…
Unified Open-World Segmentation with Multi-Modal Prompts
Yang Liu, Yufei Yin, Chenchen Jing +7
In this work, we present COSINE, a unified open-world segmentation model that consolidates open-vocabulary segmentation and in-context segmentation with multi-modal prompts (e.g.,…
scPPDM: A Diffusion Model for Single-Cell Drug-Response Prediction
Zhaokang Liang, Shuyang Zhuang, Xiaoran Jiao +3
This paper introduces the Single-Cell Perturbation Prediction Diffusion Model (scPPDM), the first diffusion-based framework for single-cell drug-response prediction from scRNA-seq…
DMark: Order-Agnostic Watermarking for Diffusion Large Language Models
Linyu Wu, Linhao Zhong, Wenjie Qu +5
Diffusion large language models (dLLMs) offer faster generation than autoregressive models while maintaining comparable quality, but existing watermarking methods fail on them due…
Evolutionary Profiles for Protein Fitness Prediction
Jigang Fan, Xiaoran Jiao, Shengdong Lin +5
Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequence space. Protein language models (pLMs…
StaMo: Unsupervised Learning of Generalizable Robot Motion from Compact State Representation
Mingyu Liu, Jiuhe Shu, Hui Chen +6
A fundamental challenge in embodied intelligence is developing expressive and compact state representations for efficient world modeling and decision making. However, existing meth…
GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert
Mingyu Liu, Zheng Huang, Xiaoyi Lin +6
Vision-language models demonstrate strong reasoning and planning abilities, yet grounding these predictions into precise robot actions remains a central challenge. Existing Vision-…
NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces
Zheng Huang, Mingyu Liu, Xiaoyi Lin +9
Vision-Language-Action (VLA) models represent a pivotal advance in embodied intelligence, yet they confront critical barriers to real-world deployment, most notably catastrophic fo…
GUI-Shepherd: Reliable Process Reward and Verification for Long-Sequence GUI Tasks
Cong Chen, Kaixiang Ji, Hao Zhong +9
Autonomous agents for long-sequence Graphical User Interface tasks are hindered by sparse rewards and the intractable credit assignment problem. To address these challenges, we int…
HieraTok: Multi-Scale Visual Tokenizer Improves Image Reconstruction and Generation
Cong Chen, Ziyuan Huang, Cheng Zou +6
In this work, we present HieraTok, a novel multi-scale Vision Transformer (ViT)-based tokenizer that overcomes the inherent limitation of modeling single-scale representations. Thi…
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
Jingqi Wu, Hanxi Li, Lin Yuanbo Wu +3
Industrial product inspection is often performed using Anomaly Detection (AD) frameworks trained solely on non-defective samples. Although defective samples can be collected during…