Abstract The Large Vision-Language Model (LVLM) field has seen significant
advancements, yet its progression has been hindered by challenges in comprehending fine …

We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that
supports long-contextual input and output. IXC-2.5 excels in various text-image …

With the rapid advancements in AI-Generated Content (AIGC) AI-Generated Images (AIGIs)
have been widely applied in entertainment education and social media. However due to the …

Vision-language models (VLMs) have made significant progress in recent visual-question-
answering (VQA) benchmarks that evaluate complex visio-linguistic reasoning. However …

Web-crawled image-text pairs are inherently noisy. Prior studies demonstrate that
semantically aligning and enriching textual descriptions of these pairs can significantly …

Motion-based controllable video generation offers the potential for creating captivating
visual content. Existing methods typically necessitate model training to encode particular …

In this work, we empirically confirm that the key reason causing such an issue is that the
training images are usually paired with short captions, leaving certain tokens easily …

In large vision-language models (LVLMs), images serve as inputs that carry a wealth of
information. As the idiom" A picture is worth a thousand words" implies, representing a …

Multimodal large language models (MLLMs) have shown promising advancements in
general visual and language understanding. However, the representation of multimodal …

Dynamic Facial Expression Recognition (DFER) is crucial for understanding human
behavior. However, current methods exhibit limited performance mainly due to the …