16 citations · 16 across the 19 of their papers we have counts for
20 papers
Physics-Aware Object-Centric SE(3) Forecasting for Real-Time Proactive Dynamic Grasping
Yirui Zhou, Hongli Xu, Ying Zheng +2
Proactive dynamic grasping requires robots to predict the future state at which physical contact will occur, rather than reacting to the currently observed object pose. But what fu…
SeqAlign3DVG: A Sequence-Aligned Benchmark and Voxel Reasoning Framework for 3D Visual Grounding
Yi Zhang, Yi Wang, Yueting Wu +3
Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect temporal ordering. We introduce Se…
TextDS: Parameter-Efficient Representation Alignment for Scene Text Detection under Distribution Shifts
Boyuan Chen, Zichen Dang, Chuang Yang +2
In real-world deployments, scene text detectors inevitably face distribution shifts beyond the training distribution. Prior work often depends on large-scale scene-text pretraining…
EVA: Editing for Versatile Alignment against Jailbreaks
Yi Wang, Hongye Qiu, Yue Xu +4
Large Language Models (LLMs) and Vision Language Models (VLMs) have demonstrated impressive capabilities but remain vulnerable to jailbreaking attacks, where adversaries exploit te…
EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding
Yuejiao Su, Xinshen Zhang, Zhen Ye +3
Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing multimodal large language mod…
Qwen-Image-VAE-2.0 Technical Report
Zekai Zhang, Deqing Li, Kuan Cao +27
We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…
Qwen-Image-2.0 Technical Report
Bing Zhao, Chenfei Wu, Deqing Li +72
We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…
LLM-Agnostic Semantic Representation Attack
Jiawei Lian, Jianhong Pan, Lefan Wang +4
Large Language Models (LLMs) increasingly employ alignment techniques to prevent harmful outputs. Despite these safeguards, attackers can circumvent them by crafting adversarial pr…
Evolution-Inspired Sample Competition for Deep Neural Network Optimization
Ying Zheng, Yiyi Zhang, Yi Wang +1
Conventional deep network training generally optimizes all samples under a largely uniform learning paradigm, without explicitly modeling the heterogeneous competition among them.…
SID-Coord: Coordinating Semantic IDs for ID-based Ranking in Short-Video Search
Guowen Li, Yuepeng Zhang, Shunyu Zhang +4
Large-scale short-video search ranking models are typically trained on sparse co-occurrence signals over hashed item identifiers (HIDs). While effective at memorizing frequent inte…
MASS: Mesh-inellipse Aligned Deformable Surfel Splatting for Hand Reconstruction and Rendering from Egocentric Monocular Video
Haoyu Zhu, Yi Zhang, Lei Yao +2
Reconstructing high-fidelity 3D hands from egocentric monocular videos remains a challenge due to the limitations in capturing high-resolution geometry, hand-object interactions, a…
HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesis
Mingjin Chen, Junhao Chen, Zhaoxin Fan +6
Recent methods have made notable progress in the visual quality of hand-object interaction video synthesis. However, most approaches rely on 2D control signals that lack spatial ex…
ProCal: Probability Calibration for Neighborhood-Guided Source-Free Domain Adaptation
Ying Zheng, Yiyi Zhang, Yi Wang +1
Source-Free Domain Adaptation (SFDA) adapts pre-trained models to unlabeled target domains without requiring access to source data. Although state-of-the-art methods leveraging loc…
Semantic Representation Attack against Aligned Large Language Models
Jiawei Lian, Jianhong Pan, Lefan Wang +3
Large Language Models (LLMs) increasingly employ alignment techniques to prevent harmful outputs. Despite these safeguards, attackers can circumvent them by crafting prompts that i…
ANNEXE: Unified Analyzing, Answering, and Pixel Grounding for Egocentric Interaction
Yuejiao Su, Yi Wang, Qiongyang Hu +2
Egocentric interaction perception is one of the essential branches in investigating human-environment interaction, which lays the basis for developing next-generation intelligent s…
Revealing the Intrinsic Ethical Vulnerability of Aligned Large Language Models
Jiawei Lian, Jianhong Pan, Lefan Wang +3
Large language models (LLMs) are foundational explorations to artificial general intelligence, yet their alignment with human values via instruction tuning and preference learning…
SignEye: Traffic Sign Interpretation from Vehicle First-Person View
Chuang Yang, Xu Han, Tao Han +5
Traffic signs play a key role in assisting autonomous driving systems (ADS) by enabling the assessment of vehicle behavior in compliance with traffic regulations and providing navi…
Attack Anything: Blind DNNs via Universal Background Adversarial Attack
Jiawei Lian, Shaohui Mei, Xiaofei Wang +5
It has been widely substantiated that deep neural networks (DNNs) are susceptible and vulnerable to adversarial perturbations. Existing studies mainly focus on performing attacks b…
A Survey of Embodied Learning for Object-Centric Robotic Manipulation
Ying Zheng, Lei Yao, Yuejiao Su +5
Embodied learning for object-centric robotic manipulation is a rapidly developing and challenging area in embodied AI. It is crucial for advancing next-generation intelligent robot…
PADetBench: Towards Benchmarking Physical Attacks against Object Detection
Jiawei Lian, Jianhong Pan, Lefan Wang +3
Physical attacks against object detection have gained increasing attention due to their significant practical implications. However, conducting physical experiments is extremely ti…