Multimodal LLMs contain an encoder, LLM, and a “connector” between the multiple modalities. The LLM is typically pre-trained. For instance, LLaVA uses the CLIP ViT-L/14 for an image encoder and Vicuna ...

With a groundbreaking fine-tuning approach, researchers bridge text and vision models to set a new standard for cross-lingual and long-caption retrieval in multimodal AI. LLM2CLIP Overview. After ...

A Solution: Encoder-Decoder Separation The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.

NVIDIA’s latest AI model, NVLM 1.0, pushes the boundaries of multimodal learning by mastering both visual and textual data, introducing powerful hybrid architectures, and setting a new standard ...

Apple has revealed its latest development in artificial intelligence (AI) large language model (LLM), introducing the MM1 family of multimodal models capable of interpreting both images and text data.

Artificial intelligence researchers from Apple Inc. and Cornell University quietly unveiled an open-source and multimodal large language model last October known as Ferret, which is said to use parts ...

Patronus AI today announced the launch of the industry's first Multimodal LLM-as-a-Judge (MLLM-as-a-Judge), a groundbreaking evaluation capability that enables developers to score and optimize ...

How multimodal prompt injection image attacks work Multimodal prompt injection attacks exploit the gaps in how GPT-4V processes visual imagery to execute malicious commands that go undetected.