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20232026
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cs.CV2026

Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification

Wujian Peng, Lingchen Meng, Yuxuan Cai +7

Unified Multimodal Modeling aims to integrate visual understanding and generation within a single system. However, existing approaches typically rely on two disparate visual tokeni…

cs.CV2026

Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization

Zhuohan Liu, Wujian Peng, Yitong Chen +1

Despite the rapid progress of text-to-image (T2I) models, generating images that accurately reflect complex compositional prompts (covering attribute bindings, object relationships…

cs.CV2025

Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Yitong Chen, Lingchen Meng, Wujian Peng +4

Vision Foundation Models (VFMs) provide strong visual representations for a wide range of applications. In this work, we enhance prevailing VFMs through multimodal training, allowi…

cs.CV2024

INST-IT: Boosting Instance Understanding via Explicit Visual Prompt Instruction Tuning

Wujian Peng, Lingchen Meng, Yitong Chen +7

Large Multimodal Models (LMMs) have made significant breakthroughs with the advancement of instruction tuning. However, while existing models can understand images and videos at a…

cs.CV2023

Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language Understanding

Wujian Peng, Sicheng Xie, Zuyao You +2

Vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attri…

cs.CV2023

Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data

Zuxuan Wu, Zejia Weng, Wujian Peng +4

Despite significant results achieved by Contrastive Language-Image Pretraining (CLIP) in zero-shot image recognition, limited effort has been made exploring its potential for zero-…