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20182026
most citedSemantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis

42 citations · 184 across the 29 of their papers we have counts for

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46 papers · 1 filter

cs.CV2026

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…

cs.CV2026

Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning

Jiahao Shao, Yuanbo Yang, Yiyi Liao +3

Tool-augmented vision-language models increasingly "think with images": they call crop, zoom, or code tools and reason over the returned pixels. However, recent work using blind te…

cs.CV2026

Representation Forcing for Bottleneck-Free Unified Multimodal Models

Yuqing Wang, Zhijie Lin, Ceyuan Yang +10

Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrained VAE for image generation…

cs.CV2026

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…

cs.CV2026

VTok: A Unified Video Tokenizer with Decoupled Spatial-Temporal Latents

Feng Wang, Yichun Shi, Ceyuan Yang +4

This work presents VTok, a unified video tokenization framework that can be used for both generation and understanding tasks. Unlike the leading vision-language systems that tokeni…

cs.CV2025

Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model

Team Seedance, Heyi Chen, Siyan Chen +194

Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…