41 citations · 359 across the 102 of their papers we have counts for
28 papers · 1 filter
ReTrace: Cross-Stage Failure Attribution for Self-Improving Robotic Manipulation
Yue Yu, Bin Zhu, Junhui Li +3
General-purpose multimodal foundation models are increasingly capable of directly controlling robots, yet improving their manipulation capabilities through autonomous interaction r…
VideoResearchAgent: Grounded Task Synthesis and Sim-to-Real RL for Open-Web Video Research
Yuhang Zhou, Fei Li, Yuxi Wu +2
Existing deep research agents are designed primarily for text- and image-based web sources, while video reasoning systems typically assume that relevant videos are provided in adva…
RoboIRGBench: Benchmarking Implicit Referential Grounding in Vision-Language-Action Models
Aernaer Akelijiang, Jiannan Li, Zhineng Chen +2
Vision-Language-Action (VLA) models have shown strong capabilities in robotic manipulation, yet existing benchmarks typically assume that task-relevant information is explicitly sp…
LIBERO-VPro: Benchmarking Closed-Loop Visual Robustness of Robotic Foundation Models
Huiqiong Li, Zhiting Mei, Anirudha Majumdar +3
Robotic foundation models achieve impressive performance on standard manipulation benchmarks, yet these evaluations typically assume clean, timely, and consistent visual observatio…
Stable and Efficient Real-World Online VLA Post-Training via Asynchronous Replay-Anchored Policy Improvement
Jiarui Yang, Jiajin Zhang, Bin Zhu +2
Online post-training of vision-language-action (VLA) models requires efficient use of robot interaction and reliable policy improvement from continually collected experience. We pr…
MoWAM: Explicit Future Motion Prediction for Efficient World Action Models
Jiayu Wang, Bin Zhu, Yue Yu +1
World Action Models (WAMs) improve robot policy learning by incorporating future dynamics, yet explicitly generating future videos at inference introduces substantial computational…
VICAL: Vicinal Consistency Alignment for Long-Tailed Visual Recognition
Jiangang Zhu, Zheng Wang, Bin Zhu +2
Multi-expert models have become the dominant paradigm for long-tailed learning, largely attributed to their presumed ability to benefit from expert diversity. However, we revisit t…
StructRL: Structured Action-Space Exploration for Flow-Based VLAs
Jiarui Yang, Bin Zhu, Jingjing Chen +4
Flow-based Vision-Language-Action (VLA) models are now widely used for continuous robotic manipulation, and online reinforcement learning (RL) is emerging as a key technique for ad…
ReGraph: Learning to Generate Recipe Graphs from Food Images
Guoshan Liu, Bin Zhu, Pengkun Jiao +3
Recent Large Multimodal Models (LMMs) have achieved impressive performance in recipe generation from food images.However, cooking is a structured transformation process in which in…
Vorch-IR: Long-Form Unified Multimodal Identity Replacement Video Generation
Yaole Wang, Xiaoyu Chen, Xin Ma +5
Video identity replacement seeks to transfer the identities of one or more subjects while preserving the motion, expressions, and temporal structure of a driving video. Existing me…
SphereVideo: Prototype-anchored Hyperspherical Boundary for Continual AI-generated Video Detection
Fei Li, Yue Yu, Yuran Wang +3
AI-generated video (AIGV) detection aims to distinguish real videos from AI-generated ones. In practice, detectors trained on existing data often fail to generalize to newly emergi…
DECODE: Tackling Representation and Decision Degradation in Continual AI-Generated Image Detection
Zihao Cai, Xinghan Li, Ruiyan Yang +3
As generative models continue to evolve, AI-generated image detectors must incrementally adapt to emerging generative domains while preserving knowledge acquired from previous ones…
Disentangling Semantic Attention from Structural Bias in the Attention Manifold
Pengkun Jiao, Bin Zhu, Jingjing Chen +1
The empirical success of attention mechanism in Multimodal Large Language Models (MLLMs) often obscures its inherent, subtle flaws. Specifically, MLLMs consistently exhibit disprop…
Adaptive Inference-Time Scaling via Early-Step Latent Verification for Image Editing
Yue Yu, Yang Jiao, Jiayu Wang +2
Instruction-based image editing has made notable progress with recent advances in generative models. However, the quality of the edited result is still influenced by the randomly s…
RoboTrustBench: Benchmarking the Trustworthiness of Video World Models for Robotic Manipulation
Huiqiong Li, Jiayu Wang, Zhiting Mei +3
Video world models are increasingly used in robotic manipulation, yet existing benchmarks mostly evaluate them under valid, feasible, and safe instructions. We introduce RoboTrustB…
Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses
Xiao Li, Xiang Zheng, Yifeng Gao +35
Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, and interaction into agents that operate in open-world, safety-critical environments. As…
TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models
Xin Wang, Yixu Wang, Jiaming Zhang +6
Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to imperceptible adversarial perturbation…
ImageAttributionBench: How Far Are We from Generalizable Attribution?
Tingshu Mou, Zhipeng Wei, Chao Gong +2
The rapid advancement of generative AI has enabled the creation of highly realistic and diverse synthetic images, posing critical challenges for image provenance and misinformation…
From Synthetic to Real: Toward Identity-Consistent Makeup Transfer with Synthetic and Real Data
Yue Yu, Jiayu Wang, Jiajia Shi +3
Makeup transfer aims to apply the makeup style of a reference portrait to a source portrait while preserving identity and background. Early methods formulate this task as unsupervi…
Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models
Ziyao Tang, Pengkun Jiao, Bin Zhu +3
Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely…
SpatialImaginer: Towards Adaptive Visual Imagination for Spatial Reasoning
Yian Li, Yang Jiao, Bin Zhu +4
Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language…
OSCBench: Benchmarking Object State Change in Text-to-Video Generation
Xianjing Han, Bin Zhu, Shiqi Hu +4
Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, existing benchmarks primarily focus on pe…
RC-NF: Robot-Conditioned Normalizing Flow for Real-Time Anomaly Detection in Robotic Manipulation
Shijie Zhou, Bin Zhu, Jiarui Yang +3
Recent advances in Vision-Language-Action (VLA) models have enabled robots to execute increasingly complex tasks. However, VLA models trained through imitation learning struggle to…
VIGIL: Part-Grounded Structured Reasoning for Generalizable Deepfake Detection
Xinghan Li, Junhao Xu, Jingjing Chen
Multimodal large language models (MLLMs) offer a promising path toward interpretable deepfake detection by generating textual explanations. However, the reasoning process of curren…