7 citations · 11 across the 4 of their papers we have counts for
4 papers
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Le Xue, Manli Shu, Anas Awadalla +30
This paper introduces BLIP-3, an open framework for developing Large Multimodal Models (LMMs). The framework comprises meticulously curated datasets, a training recipe, model archi…
Text2Data: Low-Resource Data Generation with Textual Control
Shiyu Wang, Yihao Feng, Tian Lan +6
Natural language serves as a common and straightforward signal for humans to interact seamlessly with machines. Recognizing the importance of this interface, the machine learning c…
X-InstructBLIP: A Framework for aligning X-Modal instruction-aware representations to LLMs and Emergent Cross-modal Reasoning
Artemis Panagopoulou, Le Xue, Ning Yu +7
Recent research has achieved significant advancements in visual reasoning tasks through learning image-to-language projections and leveraging the impressive reasoning abilities of…
HIVE: Harnessing Human Feedback for Instructional Visual Editing
Shu Zhang, Xinyi Yang, Yihao Feng +9
Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences. We hypothesize that state-of-the-art instructional…