We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-
Language Models that significantly improves upon its predecessor, DeepSeek-VL, through …

Despite the rapid integration of video perception capabilities into Large Multimodal Models
(LMMs), the underlying mechanisms driving their video understanding remain poorly …

We introduce MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01, which are
comparable to top-tier models while offering superior capabilities in processing longer …

We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500
real-world tasks, to address the highly heterogeneous daily use cases of end users. Our …

Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly
in languages other than English and in underrepresented cultural contexts. To evaluate their …

The intelligent dialogue system, aiming at communicating with humans harmoniously with
natural language, is brilliant for promoting the advancement of human-machine interaction …

Large language models have demonstrated impressive performance when integrated with
vision models even enabling video understanding. However, evaluating these video models …

Current large multimodal models (LMMs) face significant challenges in processing and
comprehending long-duration or high-resolution videos, which is mainly due to the lack of …

In recent years, vision language models (VLMs) have made significant advancements in
video understanding. However, a crucial capability-fine-grained motion comprehension …

Perception and understanding are two pillars of computer vision. While multimodal large
language models (MLLM) have demonstrated remarkable visual understanding capabilities …