EPFL researchers launch 4M: an open source training framework to advance multimodal AI
Multimodal core models are increasingly relevant in artificial intelligence, allowing systems to process and integrate multiple forms of data, such ...
Tag: multimodal
VITA-1.5: A multimodal large language model that integrates vision, language and speech through a carefully designed three-stage training methodology
The development of multimodal large language models (MLLM) has provided new opportunities in artificial intelligence. However, significant challenges remain in ...
ScreenSpot-Pro: The First Benchmark Driving Multimodal LLMs Towards High-Resolution Professional GUI Agent and Computer Usage Environments
GUI agents face three critical challenges in professional environments: (1) the increased complexity of professional applications compared to general-purpose software, ...
This AI paper presents XMODE: an explainable multimodal data exploration system powered by LLM to improve accuracy and efficiency
Researchers are increasingly focused on creating systems that can handle multimodal data exploration, which combines structured and unstructured data. This ...
Collective Monte Carlo Tree Search (CoMCTS): A New Reasoning Learning Method for Multimodal Large Language Models
In today's world, Multimodal Large Language Models (MLLM) are advanced systems that process and understand multiple forms of input, such ...
This AI whitepaper from the Data Provenance Initiative team highlights challenges in provenance, licensing, representation, and transparency of multimodal datasets for responsible development.
The advancement of artificial intelligence depends on the availability and quality of training data, particularly as multimodal core models gain ...
Qwen Team Releases QvQ: An Open Weight Model for Multimodal Reasoning
Multimodal reasoning (the ability to process and integrate information from diverse data sources, such as text, images, and videos) remains ...
Simplify multimodal generative AI with Amazon Bedrock Data Automation
Developers face significant challenges when using foundation models (FMs) to extract data from unstructured assets. This data extraction process requires ...
Meta AI launches Apollo: a new family of large multimodal video-LMM models for video understanding
While multimodal models (LMMs) have advanced significantly for text and image tasks, video-based models remain underdeveloped. Videos are intrinsically complex ...
Microsoft AI Research Introduces OLA-VLM: A Vision-Centric Approach to Optimizing Large Multimodal Language Models
Multimodal large language models (MLLM) are advancing rapidly, allowing machines to interpret and reason about textual and visual data simultaneously. ...
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