We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series
that builds upon InternVL 2.0, maintaining its core model architecture while introducing …

Large language model (LLM) leads to a surge of autonomous GUI agents for smartphone,
which completes a task triggered by natural language through predicting a sequence of …

Recent advances in foundation models, particularly Large Language Models (LLMs) and
Multimodal Large Language Models (MLLMs), have facilitated the development of intelligent …

Mobile agents are essential for automating tasks in complex and dynamic mobile
environments. As foundation models evolve, the demands for agents that can adapt in real …

The capability to process multiple images is crucial for Large Vision-Language Models
(LVLMs) to develop a more thorough and nuanced understanding of a scene. Recent multi …

Building a generalist model for user interface (UI) understanding is challenging due to
various foundational issues, such as platform diversity, resolution variation, and data …

Existing efforts in building GUI agents heavily rely on the availability of robust commercial
Vision-Language Models (VLMs) such as GPT-4o and GeminiProVision. Practitioners are …

Graphical User Interface (GUI) automation holds significant promise for enhancing human
productivity by assisting with digital tasks. While recent Large Language Models (LLMs) and …

In this paper, we introduce the Generalist Virtual Agent (GVA), an autonomous entity
engineered to function across diverse digital platforms and environments, assisting users by …

Building Graphical User Interface (GUI) assistants holds significant promise for enhancing
human workflow productivity. While most agents are language-based, relying on closed …