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cs.CV2026

DocReward: A Document Reward Model for Structuring and Stylizing

Junpeng Liu, Yuzhong Zhao, Bowen Cao +17

Recent agentic workflows automate professional document generation but focus narrowly on textual quality, overlooking structural and stylistic professionalism, which is equally cri…

cs.CV2026

Audio-Visual Intelligence in Large Foundation Models

You Qin, Kai Liu, Shengqiong Wu +12

Audio-Visual Intelligence (AVI) has emerged as a central frontier in artificial intelligence, bridging auditory and visual modalities to enable machines that can perceive, generate…

cs.CV2026

Synergizing Understanding and Generation with Interleaved Analyzing-Drafting Thinking

Shengqiong Wu, Bobo Li, Xinkai Wang +6

Unified Vision-Language Models (UVLMs) aim to advance multimodal learning by supporting both understanding and generation within a single framework. However, existing approaches la…

cs.CL2026

Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems

Zongqian Li, Tengchao Lv, Shaohan Huang +8

Training next-generation code generation models requires high-quality datasets, yet existing datasets face difficulty imbalance, format inconsistency, and data quality problems. We…

cs.CV2026

UniM: A Unified Any-to-Any Interleaved Multimodal Benchmark

Yanlin Li, Minghui Guo, Kaiwen Zhang +13

In real-world multimodal applications, systems usually need to comprehend arbitrarily combined and interleaved multimodal inputs from users, while also generating outputs in any in…