most citedSkillNet: Create, Evaluate, and Connect AI Skills

1 citations · 1 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety

Shikai Qiu, Xiaowen Xu, Benlei Cui +55

General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature of content and AI s…

cs.RO2026

VQActFlow: Vector-Quantized Action Mode Steering for Multi-Task Robot Manipulation

Zhigen Zhao, Mark Leggiero, Yipu Chen +5

Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitatively different action modes fro…

cs.RO2026

WT-UMI: Tactile-based Whole-Body Manipulation via Force-Supervised Contact-Aware Planning

Jaehwi Jang, Zhaoyuan Gu, Alfred Cueva +15

Whole-body humanoid manipulation of bulky, deformable, and shared-load objects requires distributed contact sensing and explicit force regulation, yet most imitation policies treat…

cs.CV2026

simpleposter: A simple baseline for product poster generation

Benlei Cui, Fangao Zeng, Weitao Jiang +6

Product poster generation poses distinct challenges beyond general poster design, requiring both faithful preservation of product appearance and precise control over dense, multi-l…

cs.CL2026

How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities

Ziwen Xu, Kewei Xu, Haoming Xu +8

Large Language Models (LLMs) are increasingly deployed in socially sensitive domains, yet their unpredictable behaviors, ranging from misaligned intent to inconsistent personality,…

cs.CV2026

SRasP: Self-Reorientation Adversarial Style Perturbation for Cross-Domain Few-Shot Learning

Wenqian Li, Pengfei Fang, Hui Xue

Cross-Domain Few-Shot Learning (CD-FSL) aims to transfer knowledge from a seen source domain to unseen target domains, serving as a key benchmark for evaluating the robustness and…

cs.AI2026★ 1 cited

SkillNet: Create, Evaluate, and Connect AI Skills

Yuan Liang, Ruobin Zhong, Haoming Xu +47

Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumulation and transfer of skills. Wi…

cs.CV2026

TC-Padé: Trajectory-Consistent Padé Approximation for Diffusion Acceleration

Benlei Cui, Shaoxuan He, Bukun Huang +8

Despite achieving state-of-the-art generation quality, diffusion models are hindered by the substantial computational burden of their iterative sampling process. While feature cach…

cs.CV2026

Diffusion Probe: Generated Image Result Prediction Using CNN Probes

Benlei Cui, Bukun Huang, Zhizeng Ye +7

Text-to-image (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation scenarios such as prompt iterat…

cs.CV2023

One-Dimensional Adapter to Rule Them All: Concepts, Diffusion Models and Erasing Applications

Mengyao Lyu, Yuhong Yang, Haiwen Hong +6

The prevalent use of commercial and open-source diffusion models (DMs) for text-to-image generation prompts risk mitigation to prevent undesired behaviors. Existing concept erasing…