1 citations · 3 across the 8 of their papers we have counts for
6 papers · 1 filter
WorldVQA: Measuring Atomic World Knowledge in Multimodal Large Language Models
Runjie Zhou, Youbo Shao, Haoyu Lu +16
We introduce WorldVQA, a benchmark designed to evaluate the atomic visual world knowledge of Multimodal Large Language Models (MLLMs). Unlike current evaluations, which often confl…
Towards Pixel-Level VLM Perception via Simple Points Prediction
Tianhui Song, Haoyu Lu, Hao Yang +8
We present SimpleSeg, a strikingly simple yet highly effective approach to endow Multimodal Large Language Models (MLLMs) with native pixel-level perception. Our method reframes se…
UI-UG: A Unified MLLM for UI Understanding and Generation
Hao Yang, Weijie Qiu, Ru Zhang +8
Although Multimodal Large Language Models (MLLMs) have been widely applied across domains, they are still facing challenges in domain-specific tasks, such as User Interface (UI) un…
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding
Renjie Li, Ruijie Ye, Mingyang Wu +4
Humans are integral components of the transportation ecosystem, and understanding their behaviors is crucial to facilitating the development of safe driving systems. Although recen…
Online Iterative Self-Alignment for Radiology Report Generation
Ting Xiao, Lei Shi, Yang Zhang +3
Radiology Report Generation (RRG) is an important research topic for relieving radiologist' heavy workload. Existing RRG models mainly rely on supervised fine-tuning (SFT) based on…
Kimi-VL Technical Report
Kimi Team, Angang Du, Bohong Yin +92
We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…