Mm-llms: Recent advances in multimodal large language models
In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …
On the challenges and perspectives of foundation models for medical image analysis
This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …
pretrained models, ie, foundation models, which promise to significantly improve the …
Adversarial diffusion distillation
A Sauer, D Lorenz, A Blattmann… - European Conference on …, 2025 - Springer
Abstract We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that
efficiently samples large-scale foundational image diffusion models in just 1–4 steps while …
efficiently samples large-scale foundational image diffusion models in just 1–4 steps while …
A foundation model for clinical-grade computational pathology and rare cancers detection
The analysis of histopathology images with artificial intelligence aims to enable clinical
decision support systems and precision medicine. The success of such applications …
decision support systems and precision medicine. The success of such applications …
How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites
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 …
(MLLM) to bridge the capability gap between open-source and proprietary commercial …
Depth anything: Unleashing the power of large-scale unlabeled data
Abstract This work presents Depth Anything a highly practical solution for robust monocular
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
MM1: methods, analysis and insights from multimodal LLM pre-training
In this work, we discuss building performant Multimodal Large Language Models (MLLMs).
In particular, we study the importance of various architecture components and data choices …
In particular, we study the importance of various architecture components and data choices …
A survey on multimodal large language models
Multimodal Large Language Model (MLLM) recently has been a new rising research
hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform …
hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform …
End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
Anydoor: Zero-shot object-level image customization
This work presents AnyDoor a diffusion-based image generator with the power to teleport
target objects to new scenes at user-specified locations with desired shapes. Instead of …
target objects to new scenes at user-specified locations with desired shapes. Instead of …