activity
20242026
collaborators

12 papers

cs.CV2026

Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation

Chonghuinan Wang, Zhikai Chen, Chunwei Wang +9

The advancement of generative AI models capable of producing text and image marks a critical step forward in the realm of multimodal intelligence, particularly for tasks involving…

cs.AI2026

IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation

Lingyi Meng, Zecong Tang, Haoran Li +12

In recent years, unified multimodal models (UMMs) have emerged to support both understanding and generation within a single framework. Mastering dynamic, multi-turn interleaved ima…

cs.CV2026

InterCoG: Towards Spatially Precise Image Editing with Interleaved Chain-of-Grounding Reasoning

Yecong Wan, Fan Li, Chunwei Wang +3

Emerging unified editing models have demonstrated strong capabilities in general object editing tasks. However, it remains a significant challenge to perform fine-grained editing i…

cs.CV2026

Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization

Ming Nie, Chunwei Wang, Jianhua Han +2

Unified vision-language models have made significant progress in multimodal understanding and generation, yet they largely fall short in producing multimodal interleaved outputs, w…

cs.CV2026

SemHiTok: A Unified Image Tokenizer via Semantic-Guided Hierarchical Codebook for Multimodal Understanding and Generation

Zisheng Chen, Chunwei Wang, Runhui Huang +6

In this paper, we introduce SemHiTok, a unified image Tokenizer via Semantic-Guided Hierarchical codebook that provides consistent discrete representations for multimodal understan…

cs.CV2026

SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM

Ming Nie, Dan Ding, Chunwei Wang +4

Large language models (LLMs) have demonstrated exceptional capabilities in text understanding, which has paved the way for their expansion into video LLMs (Vid-LLMs) to analyze vid…