Search Results for author:
Found 3 papers, 3 papers with code
SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models
We present SPHINX, a versatile multi-modal large language model (MLLM) with a joint mixing of model weights, tuning tasks, and visual embeddings.
Ranked #2 on
Visual Question Answering
on BenchLMM
(using extra training data)
ImageBind-LLM: Multi-modality Instruction Tuning
During training, we adopt a learnable bind network to align the embedding space between LLaMA and ImageBind's image encoder.
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
We present LLaMA-Adapter, a lightweight adaption method to efficiently fine-tune LLaMA into an instruction-following model.
Ranked #2 on
Music Question Answering
on MusicQA
