23 papers
DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing
Zhaokai Wang, Mingxin Liu, Zirun Zhu +11
Recent image generation and editing models can produce visually appealing natural images, yet they remain unreliable when the target image is a knowledge-intensive diagram whose co…
ACE: Pluggable Adaptive Context Elasticizer across Agents
Ning Liao, Zihao Long, Xiaoxing Wang +6
The increasing complexity of agentic tasks has led to rapidly growing trajectory lengths, which poses significant challenges for large language model (LLM) based agents with fixed…
SparseX: Efficient Segment-Level KV Cache Sharing for Interleaved LLM Serving
Quqing Zhang, Kai Chen, Ning Liao +5
In long-context LLM serving, the prefill stage often dominates time-to-first-token and computational cost. Although Prefix Cache in vLLM/PagedAttention has been widely used to reus…
MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation
Yan Li, Zezi Zeng, Yifan Yang +12
The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for webpage design, offering a flexi…
GRADE: Benchmarking Discipline-Informed Reasoning in Image Editing
Mingxin Liu, Ziqian Fan, Zhaokai Wang +13
Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natural images and shallow commonsense…
EvoTok: A Unified Image Tokenizer via Residual Latent Evolution for Visual Understanding and Generation
Yan Li, Ning Liao, Xiangyu Zhao +5
The development of unified multimodal large language models (MLLMs) is fundamentally challenged by the granularity gap between visual understanding and generation: understanding re…