1 citations · 1 across the 15 of their papers we have counts for
7 papers · 1 filter
LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
Yicheng Xiao, Lin Song, Rui Yang +4
Recent advances have highlighted the benefits of scaling language models to enhance performance across a wide range of NLP tasks. However, these approaches still face limitations i…
MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
Yicheng Xiao, Lin Song, Yukang Chen +7
Recent text-to-image systems face limitations in handling multimodal inputs and complex reasoning tasks. We introduce MindOmni, a unified multimodal large language model that addre…
HaploOmni: Unified Single Transformer for Multimodal Video Understanding and Generation
Yicheng Xiao, Lin Song, Rui Yang +6
With the advancement of language models, unified multimodal understanding and generation have made significant strides, with model architectures evolving from separated components…
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning
Jiaqi Huang, Zunnan Xu, Jun Zhou +6
Leveraging multimodal large models for image segmentation has become a prominent research direction. However, existing approaches typically rely heavily on manually annotated datas…
From Prediction to Perfection: Introducing Refinement to Autoregressive Image Generation
Cheng Cheng, Lin Song, Di An +4
Autoregressive (AR) image generators offer a language-model-friendly approach to image generation by predicting discrete image tokens in a causal sequence. However, unlike diffusio…
TransDiff: Diffusion-Based Method for Manipulating Transparent Objects Using a Single RGB-D Image
Haoxiao Wang, Kaichen Zhou, Binrui Gu +6
Manipulating transparent objects presents significant challenges due to the complexities introduced by their reflection and refraction properties, which considerably hinder the acc…
HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding
Rui Yang, Lin Song, Yicheng Xiao +4
Recent advancements in large language models (LLMs) have significantly propelled the development of large multi-modal models (LMMs), highlighting the potential for general and inte…