6 citations · 6 across the 5 of their papers we have counts for
6 papers
SenseNova-U1.5: Towards Native Unified Visual Intelligence
Haiwen Diao, Jiahao Wang, Chenjing Ding +62
We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture.…
ACPO: Counteracting Likelihood Displacement in Vision-Language Alignment with Asymmetric Constraints
Kaili Huang, Hongming Zhang, Rui Shen +4
While Direct Preference Optimization (DPO) has become the de facto approach for aligning Large Vision-Language Models (LVLMs), it suffers from Likelihood Displacement, where the pr…
I2E: From Image Pixels to Actionable Interactive Environments for Text-Guided Image Editing
Jinghan Yu, Junhao Xiao, Chenyu Zhu +9
Existing text-guided image editing methods primarily rely on end-to-end pixel-level inpainting paradigm. Despite its success in simple scenarios, this paradigm still significantly…
InteractiveOmni: A Unified Omni-modal Model for Audio-Visual Multi-turn Dialogue
Wenwen Tong, Hewei Guo, Dongchuan Ran +23
We introduce InteractiveOmni, a unified and open-source omni-modal large language model for audio-visual multi-turn interaction, ranging from 4B to 8B parameters, designed to lead…
HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving
Zhiwen Chen, Bo Leng, Zhuoren Li +4
Integrating Large Language Models (LLMs) with Reinforcement Learning (RL) can enhance autonomous driving (AD) performance in complex scenarios. However, current LLM-Dominated RL me…
M2DA: Multi-Modal Fusion Transformer Incorporating Driver Attention for Autonomous Driving
Dongyang Xu, Haokun Li, Qingfan Wang +3
End-to-end autonomous driving has witnessed remarkable progress. However, the extensive deployment of autonomous vehicles has yet to be realized, primarily due to 1) inefficient mu…