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20242026
most citedHTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models

1 citations · 2 across the 12 of their papers we have counts for

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cond-mat.supr-con2026

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,…

cs.CV2026

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…

cs.AI2026

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,…

cs.CV2026

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…

cs.CL2026

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…

cs.CV2026

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…

cs.CL2026

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…

cs.CV2026

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…