Multimodal large language models (MLLMs) building upon the foundation of powerful large
language models (LLMs) have recently demonstrated exceptional capabilities in generating …

Large multimodal models demonstrate remarkable generalist ability to perform diverse
multimodal tasks in a zero-shot manner. Large-scale web-based image-text pairs contribute …

Current instruction-based image editing methods such as InstructPix2Pix often fail to
produce satisfactory results in complex scenarios due to their dependence on the simple …

In this work, we introduce Mini-Gemini, a simple and effective framework enhancing multi-
modality Vision Language Models (VLMs). Despite the advancements in VLMs facilitating …

Connecting text and visual modalities plays an essential role in generative intelligence. For
this reason, inspired by the success of large language models, significant research efforts …

Existing information retrieval (IR) models often assume a homogeneous format, limiting their
applicability to diverse user needs, such as searching for images with text descriptions …

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

In this paper, we introduce Janus, an autoregressive framework that unifies multimodal
understanding and generation. Prior research often relies on a single visual encoder for …

Counterfactual reasoning a fundamental aspect of human cognition involves contemplating
alternatives to established facts or past events significantly enhancing our abilities in …

Humans generally acquire new skills without compromising the old; however, the opposite
holds for Large Language Models (LLMs), eg, from LLaMA to CodeLLaMA. To this end, we …