This paper surveys research works in the quickly advancing field of instruction tuning (IT), a
crucial technique to enhance the capabilities and controllability of large language models …

Large AI models, or foundation models, are models recently emerging with massive scales
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Fine-tuning on instruction data has been widely validated as an effective practice for
implementing chat language models like ChatGPT. Scaling the diversity and quality of such …

In this paper, we unveil that Language Models (LMs) can acquire new capabilities by
assimilating parameters from homologous models without retraining or GPUs. We first …

Large Language Models (LLMs) have revolutionized natural language processing tasks with
remarkable success. However, their formidable size and computational demands present …

In this paper, we introduce a unified and generalist Biomedical Generative Pre-trained
Transformer (BiomedGPT) model, which leverages self-supervision on large and diverse …

In a surprising turn, Large Language Models (LLMs) together with a growing arsenal of
prompt-based heuristics now offer powerful off-the-shelf approaches providing few-shot …

Despite that the segment anything model (SAM) achieved impressive results on general-
purpose semantic segmentation with strong generalization ability on daily images, its …

Prediction methods inputting embeddings from protein language models have reached or
even surpassed state-of-the-art performance on many protein prediction tasks. In natural …