1 citations · 1 across the 5 of their papers we have counts for
5 papers
MOSS-VL Technical Report
Pengyu Wang, Chenkun Tan, Shaojun Zhou +29
We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability. It is co-designed across th…
MOSS-Video-Preview: Toward Real-Time Video Understanding via Cross-Attention
Pengyu Wang, Chenkun Tan, Shaojun Zhou +18
Video understanding is shifting from the offline paradigm -- taking a fully recorded video as input and producing a single answer after it ends -- toward real-time interaction, in…
Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation
Zixuan Jiang, Yanqiao Zhu, Peng Wang +8
Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly important front-end for LLM-based assistants and agents. However, most cur…
Understanding the Role of LLMs in Multimodal Evaluation Benchmarks
Botian Jiang, Lei Li, Xiaonan Li +5
The rapid advancement of Multimodal Large Language Models (MLLMs) has been accompanied by the development of various benchmarks to evaluate their capabilities. However, the true na…
GAOKAO-MM: A Chinese Human-Level Benchmark for Multimodal Models Evaluation
Yi Zong, Xipeng Qiu
The Large Vision-Language Models (LVLMs) have demonstrated great abilities in image perception and language understanding. However, existing multimodal benchmarks focus on primary…