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20242026
most citedEmerging Properties in Unified Multimodal Pretraining

1 citations · 2 across the 11 of their papers we have counts for

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5 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

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…

cs.CV2026

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.…

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.LG2026

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…