13 papers · 1 filter
AVCap: Reinforcing Audio-Video Joint Caption with Detail-Aware Reward
Mingyang Wu, Kaituo Feng, Bohao Li +3
Detailed audio-video joint captioning is essential for multimodal video understanding and generation. However, prior works are constrained by three main limitations: (1) the scarci…
JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents
Yunlong Lin, Zixu Lin, Zhaohu Xing +23
Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, aud…
Twins: Learn to Predict Unified Representations with Focal Loss
Kaixiong Gong, Xin Cai, Bin Lin +9
Unified multimodal models seek a shared visual token space that supports both multimodal understanding and image generation. Discrete methods unify the interface via a shared codeb…
From Web to Pixels: Bringing Agentic Search into Visual Perception
Bokang Yang, Xinyi Sun, Kaituo Feng +3
Visual perception connects high-level semantic understanding to pixel-level perception, but most existing settings assume that the decisive evidence for identifying a target is alr…
GIDE: Unlocking Diffusion LLMs for Precise Training-Free Image Editing
Zifeng Zhu, Jiaming Han, Jiaxiang Zhao +2
While Diffusion Large Language Models (DLLMs) have demonstrated remarkable capabilities in multi-modal generation, performing precise, training-free image editing remains an open c…
BitDance: Scaling Autoregressive Generative Models with Binary Tokens
Yuang Ai, Jiaming Han, Shaobin Zhuang +8
We present BitDance, a scalable autoregressive (AR) image generator that predicts binary visual tokens instead of codebook indices. With high-entropy binary latents, BitDance lets…
UniWeTok: An Unified Binary Tokenizer with Codebook Size for Unified Multimodal Large Language Model
Shaobin Zhuang, Yuang Ai, Jiaming Han +12
Unified Multimodal Large Language Models (MLLMs) require a visual representation that simultaneously supports high-fidelity reconstruction, complex semantic extraction, and generat…
Growing Visual Generative Capacity for Pre-Trained MLLMs
Hanyu Wang, Jiaming Han, Ziyan Yang +6
Multimodal large language models (MLLMs) extend the success of language models to visual understanding, and recent efforts have sought to build unified MLLMs that support both unde…
Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representations
Jiaming Han, Hao Chen, Yang Zhao +6
This paper presents a multimodal framework that attempts to unify visual understanding and generation within a shared discrete semantic representation. At its core is the Text-Alig…
Unleashing Vecset Diffusion Model for Fast Shape Generation
Zeqiang Lai, Yunfei Zhao, Zibo Zhao +10
3D shape generation has greatly flourished through the development of so-called "native" 3D diffusion, particularly through the Vecset Diffusion Model (VDM). While recent advanceme…
Video-R1: Reinforcing Video Reasoning in MLLMs
Kaituo Feng, Kaixiong Gong, Bohao Li +7
Inspired by DeepSeek-R1's success in eliciting reasoning abilities through rule-based reinforcement learning (RL), we introduce Video-R1 as the first attempt to systematically expl…
AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information?
Kaixiong Gong, Kaituo Feng, Bohao Li +8
Recently, multimodal large language models (MLLMs), such as GPT-4o, Gemini 1.5 Pro, and Reka Core, have expanded their capabilities to include vision and audio modalities. While th…
RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models
Haoran Hao, Jiaming Han, Changsheng Li +2
The development of large language models (LLMs) has significantly enhanced the capabilities of multimodal LLMs (MLLMs) as general assistants. However, lack of user-specific knowled…