In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

Large Language Models (LLMs) have introduced a new era of proficiency in comprehending
complex healthcare and biomedical topics. However, there is a noticeable lack of models in …

Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

With the deepening of research on Large Language Models (LLMs), significant progress has
been made in recent years on the development of Large Multimodal Models (LMMs), which …

The rapid development of Multimodal Large Language Models (MLLMs) like GPT-4V has
marked a significant step towards artificial general intelligence. Existing methods mainly …

We introduce Visual Caption Restoration (VCR), a novel vision-language task that
challenges models to accurately restore partially obscured texts using pixel-level hints within …

Multimodal Large Language Models (MLLMs) have exhibited impressive capabilities in
visual understanding and reasoning, providing sightly reasonable answers, such as image …

The advances of large foundation models necessitate wide-coverage, low-cost, and zero-
contamination benchmarks. Despite continuous exploration of language model evaluations …

We introduce MIA-Bench, a new benchmark designed to evaluate multimodal large
language models (MLLMs) on their ability to strictly adhere to complex instructions. Our …

We present SOLO, a single transformer for Scalable visiOn-Language mOdeling. Current
large vision-language models (LVLMs) such as LLaVA mostly employ heterogeneous …