In this paper, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …

While next-token prediction is considered a promising path towards artificial general
intelligence, it has struggled to excel in multimodal tasks, which are still dominated by …

We present a unified transformer, ie, Show-o, that unifies multimodal understanding and
generation. Unlike fully autoregressive models, Show-o unifies autoregressive and …

This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

We present Lumina-mGPT, a family of multimodal autoregressive models capable of various
vision and language tasks, particularly excelling in generating flexible photorealistic images …

Existing Multimodal Large Language Models (MLLMs) increasingly emphasize complex
understanding of various visual elements, including multiple objects, text information, and …

Current artificial intelligence (AI) models often focus on enhancing performance through
meticulous parameter tuning and optimization techniques. However, the fundamental design …

Building on the foundations of language modeling in natural language processing, Next
Token Prediction (NTP) has evolved into a versatile training objective for machine learning …

Personalized image generation holds great promise in assisting humans in everyday work
and life due to its impressive function in creatively generating personalized content …

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