This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

Abstract Low-Rank Adaptation (LoRA), which updates the dense neural network layers with
pluggable low-rank matrices, is one of the best performed parameter efficient fine-tuning …

Instruction tuning of Large Vision-language Models (LVLMs) has revolutionized the
development of versatile models with zero-shot generalization across a wide range of …

With the advance of artificial intelligence (AI), the concept of interactive AI (IAI) has been
introduced, which can interactively understand and respond not only to human user input …

It is a long-lasting goal to design a generalist-embodied agent that can follow diverse
instructions in human-like ways. However, existing approaches often fail to steadily follow …

Large 2D vision-language models (2D-LLMs) have gained significant attention by bridging
Large Language Models (LLMs) with images using a simple projector. Inspired by their …

In this work, we present TextHarmony, a unified and versatile multimodal generative model
proficient in comprehending and generating visual text. Simultaneously generating images …

Supervised fine-tuning (SFT) is a crucial step for large language models (LLMs), enabling
them to align with human instructions and enhance their capabilities in downstream tasks …

As the capabilities of large language models (LLMs) have expanded dramatically, aligning
these models with human values presents a significant challenge. Traditional alignment …

Multimodal large language models (MLLMs) have demonstrated impressive capabilities
across various vision-language tasks. However, a generalist MLLM typically underperforms …