1 citations · 2 across the 12 of their papers we have counts for
17 papers
Nodal nematic superconductivity in moiré graphene
Shuwen Sun, Grgur Palle, Kenji Watanabe +4
Unconventional superconductivity can emerge in various forms in strongly correlated systems. Historically, the most extensively studied examples include nodal and triplet pairing,…
Visual-Invariance-Augmented Feature Optimal Alignment for Transferable Adversarial Attacks against Closed-Source MLLMs
Xiaojun Jia, Simeng Qin, Yiming Li +5
Multimodal large language models (MLLMs) remain vulnerable to transferable adversarial examples, especially in black-box settings where only open-source surrogate models are access…
SoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness
Haozhe Liu, Tian Ye, Sensen Gao +11
As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into long trajectories of reasoning,…
PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space
Sensen Gao, Zhaoqing Wang, Qihang Cao +3
3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generation. Recent works attempt to…
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
Kewei Zhang, Jin Wang, Sensen Gao +9
End-to-end autonomous driving via Vision-Language-Action (VLA) models demands a precarious balance between high-fidelity trajectory planning and efficient inference. Existing parad…
Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective
Weijie Wang, Qihang Cao, Sensen Gao +10
Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and interacting with the physical…
Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM
Chengyue Wu, Shiyi Lan, Yonggan Fu +9
Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference throughput. This limitation is…
OneWorld: Taming Scene Generation with 3D Unified Representation Autoencoder
Sensen Gao, Zhaoqing Wang, Qihang Cao +5
Existing diffusion-based 3D scene generation methods primarily operate in 2D image/video latent spaces, which makes maintaining cross-view appearance and geometric consistency inhe…
Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding
Sensen Gao, Shanshan Zhao, Xu Jiang +7
Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines feeding Large Language Models (…
Ovis2.5 Technical Report
Shiyin Lu, Yang Li, Yu Xia +39
We present Ovis2.5, a successor to Ovis2 designed for native-resolution visual perception and strong multimodal reasoning. Ovis2.5 integrates a native-resolution vision transformer…
Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment
Xiaojun Jia, Sensen Gao, Simeng Qin +7
Multimodal large language models (MLLMs) remain vulnerable to transferable adversarial examples. While existing methods typically achieve targeted attacks by aligning global featur…
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Xiaojun Jia, Sensen Gao, Simeng Qin +6
Large pre-trained vision-language models (VLMs), such as CLIP, demonstrate impressive generalization but remain highly vulnerable to adversarial examples (AEs). Previous work has e…
Hyper3D: Efficient 3D Representation via Hybrid Triplane and Octree Feature for Enhanced 3D Shape Variational Auto-Encoders
Jingyu Guo, Sensen Gao, Jia-Wang Bian +4
Recent 3D content generation pipelines often leverage Variational Autoencoders (VAEs) to encode shapes into compact latent representations, facilitating diffusion-based generation.…
Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack
Xiaojun Jia, Sensen Gao, Qing Guo +6
Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of tra…
HTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models
Sensen Gao, Xiaojun Jia, Yihao Huang +5
Text-to-Image(T2I) models have achieved remarkable success in image generation and editing, yet these models still have many potential issues, particularly in generating inappropri…
Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography
Nhat Chung, Sensen Gao, Tuan-Anh Vu +5
Vision-Large-Language-Models (Vision-LLMs) are increasingly being integrated into autonomous driving (AD) systems due to their advanced visual-language reasoning capabilities, targ…
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial Trajectory
Sensen Gao, Xiaojun Jia, Xuhong Ren +2
Vision-language pre-training (VLP) models exhibit remarkable capabilities in comprehending both images and text, yet they remain susceptible to multimodal adversarial examples (AEs…