1 citations · 2 across the 11 of their papers we have counts for
12 papers
VoT: Vision-of-Thought for Unified Multimodal Representation Alignment
Jingxiang Sun, Chao Liao, Zhengxiong Luo +6
Current text-to-image systems typically employ a "text encoder plus diffusion decoder" paradigm, in which text semantics directly modulate continuous latent noise. Despite their su…
Scaling Properties of Text Conditioning in Visual Generation
Zilong Chen, Chaorui Deng, Kunchang Li +2
We study empirical scaling properties for text conditioning in visual generation. Such properties have rarely been measured because diffusion loss does not scale with the number of…
ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations
Junke Wang, Xiao Wang, Jiacheng Pan +16
This paper introduces ARM, a discrete representation-based AutoRegressive Model that unifies image understanding, generation, and editing within a next-token prediction framework.…
Context Unrolling in Omni Models
Ceyuan Yang, Zhijie Lin, Yang Zhao +16
We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representations. We find that such train…
Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders
Ziliang Zhao, Bi Xue, Emma Lin +17
Embedding tables are critical components of large-scale recommendation systems, facilitating the efficient mapping of high-cardinality categorical features into dense vector repres…
Understanding and Harnessing Sparsity in Unified Multimodal Models
Shwai He, Chaorui Deng, Ang Li +1
Large multimodal models have achieved remarkable progress in both understanding and generation. Recent efforts pursue unified multimodal models that integrate heterogeneous compone…
VQ-VA World: Towards High-Quality Visual Question-Visual Answering
Chenhui Gou, Zilong Chen, Zeyu Wang +10
This paper studies Visual Question-Visual Answering (VQ-VA): generating an image, rather than text, in response to a visual question -- an ability that has recently emerged in prop…
LightFusion: A Light-weighted, Double Fusion Framework for Unified Multimodal Understanding and Generation
Zeyu Wang, Zilong Chen, Chenhui Gou +8
Unified multimodal models have recently shown remarkable gains in both capability and versatility, yet most leading systems are still trained from scratch and require substantial c…
When Visualizing is the First Step to Reasoning: MIRA, a Benchmark for Visual Chain-of-Thought
Yiyang Zhou, Haoqin Tu, Zijun Wang +11
We propose MIRA, a new benchmark designed to evaluate models in scenarios where generating intermediate visual images is essential for successful reasoning. Unlike traditional CoT…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
Emerging Properties in Unified Multimodal Pretraining
Chaorui Deng, Deyao Zhu, Kunchang Li +9
Unifying multimodal understanding and generation has shown impressive capabilities in cutting-edge proprietary systems. In this work, we introduce BAGEL, an open-source foundationa…
Causal Diffusion Transformers for Generative Modeling
Chaorui Deng, Deyao Zhu, Kunchang Li +2
We introduce Causal Diffusion as the autoregressive (AR) counterpart of Diffusion models. It is a next-token(s) forecasting framework that is friendly to both discrete and continuo…