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Found 7 papers, 7 papers with code
Semi-supervised Open-World Object Detection
We demonstrate the effectiveness of our SS-OWOD problem setting and approach for remote sensing object detection, proposing carefully curated splits and baseline performance evaluations.
BiMediX: Bilingual Medical Mixture of Experts LLM
In this paper, we introduce BiMediX, the first bilingual medical mixture of experts LLM designed for seamless interaction in both English and Arabic.
Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLM
To this end, we propose a light-weight Arabic Mini-ClimateGPT that is built on an open-source LLM and is specifically fine-tuned on a conversational-style instruction tuning curated Arabic dataset Clima500-Instruct with over 500k instructions about climate change and sustainability.
GLaMM: Pixel Grounding Large Multimodal Model
In this work, we present Grounding LMM (GLaMM), the first model that can generate natural language responses seamlessly intertwined with corresponding object segmentation masks.
XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models
The latest breakthroughs in large vision-language models, such as Bard and GPT-4, have showcased extraordinary abilities in performing a wide range of tasks.
An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers
However, the CNN feature maps still maintain the spatial relationship and we utilize this property to design self-supervised learning approaches to train the encoder of object detection transformers in pretraining and multi-task learning settings.
MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages
These models are pre-trained in a self-supervised fashion with a large English text corpus and further fine-tuned with a massive English QA dataset (e. g., SQuAD).
