collaborators

7 papers

cs.CV2026

UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models

Jiaqi Wang, Haoge Deng, Ting Pan +5

Uniform Discrete Diffusion Model (UDM) has recently emerged as a promising paradigm for discrete generative modeling; however, its integration with reinforcement learning remains l…

cs.CV2026

LINA: Linear Autoregressive Image Generative Models with Continuous Tokens

Jiahao Wang, Ting Pan, Haoge Deng +4

Autoregressive models with continuous tokens form a promising paradigm for visual generation, especially for text-to-image (T2I) synthesis, but they suffer from high computational…

cs.CV2025

Emu3.5: Native Multimodal Models are World Learners

Yufeng Cui, Honghao Chen, Haoge Deng +20

We introduce Emu3.5, a large-scale multimodal world model that natively predicts the next state across vision and language. Emu3.5 is pre-trained end-to-end with a unified next-tok…

cs.CV2025

Uniform Discrete Diffusion with Metric Path for Video Generation

Haoge Deng, Ting Pan, Fan Zhang +8

Continuous-space video generation has advanced rapidly, while discrete approaches lag behind due to error accumulation and long-context inconsistency. In this work, we revisit disc…

cs.CR2025

PiCo: Jailbreaking Multimodal Large Language Models via Pictorial Code Contextualization

Aofan Liu, Lulu Tang, Ting Pan +3

Multimodal Large Language Models (MLLMs), which integrate vision and other modalities into Large Language Models (LLMs), significantly enhance AI capabilities but also introduce ne…

cs.CV2025

EVEv2: Improved Baselines for Encoder-Free Vision-Language Models

Haiwen Diao, Xiaotong Li, Yufeng Cui +6

Existing encoder-free vision-language models (VLMs) are rapidly narrowing the performance gap with their encoder-based counterparts, highlighting the promising potential for unifie…