What Makes Multimodal In-Context Learning Work?
Abstract Large Language Models have demonstrated remarkable performance across
various tasks exhibiting the capacity to swiftly acquire new skills such as through In-Context …
various tasks exhibiting the capacity to swiftly acquire new skills such as through In-Context …
Building and better understanding vision-language models: insights and future directions
H Laurençon, A Marafioti, V Sanh… - arXiv preprint arXiv …, 2024 - arxiv.org
The field of vision-language models (VLMs), which take images and texts as inputs and
output texts, is rapidly evolving and has yet to reach consensus on several key aspects of …
output texts, is rapidly evolving and has yet to reach consensus on several key aspects of …
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective
The rapid development of large language models (LLMs) has been witnessed in recent
years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from …
years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from …
FreeSeg-Diff: Training-Free Open-Vocabulary Segmentation with Diffusion Models
Foundation models have exhibited unprecedented capabilities in tackling many domains
and tasks. Models such as CLIP are currently widely used to bridge cross-modal …
and tasks. Models such as CLIP are currently widely used to bridge cross-modal …
A Concept-Based Explainability Framework for Large Multimodal Models
Large multimodal models (LMMs) combine unimodal encoders and large language models
(LLMs) to perform multimodal tasks. Despite recent advancements towards the …
(LLMs) to perform multimodal tasks. Despite recent advancements towards the …