works on

From the 1 of 23 linked papers with an AI index.

activity
20242026
collaborators

23 papers

cs.CV2026

SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense

Siyuan Liang, Yupeng Qiu, Junfeng Fang +3

Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment, leading them to produce harmful or inappropriate content. Existing defense appro…

cs.AI2026

Branch2Skill: Efficient Skill Evolution Through Reasoning Trees

Yanwei Ren, Haotian Zhang, Likang Xiao +5

Skill evolution improves agent skills through feedback over time, with failed trajectories often providing informative signals by revealing incomplete or misleading behaviors. Howe…

cs.CV2026

MobileSAM2: Lightweight Segment Anything for Spatial Intelligence

Kai Jiang, Jiaxing Huang, Jingyi Zhang +5

The paper introduces MobileSAM2, a lightweight version of the SAM2 segmentation model designed for mobile devices, using hypergraph-based knowledge distillation to transfer tempora…

cs.AI2026

OpenClaw-Skill: Collective Skill Tree Search for Agentic Large Language Models

Tianyi Lin, Chuanyu Sun, Jingyi Zhang +6

Equipping Large Language Model (LLM) agents with effective skills is crucial for solving complex tasks in real-world systems like OpenClaw. In this work, we aim to develop a framew…

cs.LG2026

R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?

Jingyi Zhang, Tianyi Lin, Huanjin Yao +3

In this work, we aim to develop effective data synthesis techniques that autonomously synthesize multimodal training data for enhancing MLLMs in solving complex real-world tasks. T…

cs.CL2026

A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models

Junjie Zhang, Guozheng Ma, Shunyu Liu +6

Reinforcement Learning with Verifiable Rewards~(RLVR) has emerged as a powerful learn-to-reason paradigm for large reasoning models to tackle complex tasks. However, the current RL…