ru
Feedback
Artificial Intelligence l l AI Updates

Artificial Intelligence l l AI Updates

Открыть в Telegram
1 615
Подписчики
Нет данных24 часа
+47 дней
+530 день
Архив постов
🔗 GitHub_Link ❇️ Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models #VLMs Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Data processing with ML and LLM 🔥 #LLMs Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence
🔗 GitHub_Link ❇️ Data processing with ML and LLM 🔥 #LLMs Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ VIA: A Spatiotemporal Video Adaptation Framework for Global and Local Video Editing 🔥 #VideoEditing Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Awesome Evaluation of Visual Generation 🔥 Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligen
🔗 GitHub_Link ❇️ Awesome Evaluation of Visual Generation 🔥 Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link 🔗 Blog_Link NVIDIA introduces DoRA (Weight-Decomposed Low-Rank Adaptation), a high-performing alternative to
🔗 GitHub_Link 🔗 Blog_Link NVIDIA introduces DoRA (Weight-Decomposed Low-Rank Adaptation), a high-performing alternative to LoRA for fine-tuning. Key highlights: - DoRA consistently outperforms LoRA across various tasks, including commonsense reasoning, multi-turn benchmarks, and image-text understanding. - It improves both learning capacity and stability without introducing additional inference overhead. - Excels in LLM, VLM, compressed LLM, and #diffusion model applications. - It's designed to work seamlessly with existing LoRA implementations DoRA decomposes #pretrained weights into magnitude and directional components, allowing for more nuanced fine-tuning. This method closely mimics full fine-tuning behavior while maintaining the parameter efficiency of LoRA. Hugging Face #developers can easily implement DoRA by setting 'use_dora=True' in their LoraConfig, making it readily accessible to improve LLM. Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Odd-One-Out: Anomaly Detection by Comparing with Neighbors ⚡️ #AnomalyDetection Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link RT-DETR is now supported in Hugging Face Transformers! 🙌 RT-DETR, short for “Real-Time DEtection TRansformer”, is a computer vision model developed at Peking University and Baidu, Inc. capable of real-time object detection. The authors claim better performance than YOLO models in both speed and accuracy. The model comes with an Apache 2.0 license, meaning people can freely use it for commercial applications. 🔥 RT-DETR is a follow-up work of DETR, a model developed by AI at Meta that successfully used Transformers for the first time for object detection. The latter has been in the Transformers library since 2020. After this, lots of improvements have been made to enable faster convergence and inference speed. RT-DETR is an important example of that as it unlocks real-time inference at high accuracy! Big congrats to Daniel Choi for contributing this model! Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Doduo: Dense Visual Correspondence from Unsupervised Semantic-Aware Flow #UnsupervisedLearning Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ GiT: the first successful LLM-like general vision model unifies various vision tasks only with a vanilla Vi
🔗 GitHub_Link ❇️ GiT: the first successful LLM-like general vision model unifies various vision tasks only with a vanilla ViT 💥 #LLMs #ViT Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Large-Vocabulary Continuous Sign Language Recognition Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial
🔗 GitHub_Link ❇️ Large-Vocabulary Continuous Sign Language Recognition Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ ManiWAV: Learning Robot Manipulation from In-the-Wild Audio-Visual Data #Robotics Join my channel: 👇👇👇👇
🔗 GitHub_Link ❇️ ManiWAV: Learning Robot Manipulation from In-the-Wild Audio-Visual Data #Robotics Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ OPTIMUS: Imitating Task and Motion Planning with Visuomotor Transformers #Robotics Join my channel: 👇👇👇�
🔗 GitHub_Link ❇️ OPTIMUS: Imitating Task and Motion Planning with Visuomotor Transformers #Robotics Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ UniDexGrasp++: Improving Dexterous Grasping Policy Learning via Geometry-aware Curriculum and Iterative Gen
🔗 GitHub_Link ❇️ UniDexGrasp++: Improving Dexterous Grasping Policy Learning via Geometry-aware Curriculum and Iterative Generalist-Specialist Learning #Robotics Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks #Robotics Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Dex Retargeting: Various retargeting optimizers to translate human hand motion to robot hand motion #MotionRetargeting Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ Generative Region-Language Pretraining for Open-Ended Object Detection #ObjectDetection Join my channel: 👇
🔗 GitHub_Link ❇️ Generative Region-Language Pretraining for Open-Ended Object Detection #ObjectDetection Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild #NeRF Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration Join my
🔗 GitHub_Link ❇️ From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects #3D #ObjectDetection Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates

🔗 GitHub_Link ❇️ AsyncDepth: Better Monocular 3D Detectors with LiDAR from the Past #LiDAR #Depth #3D Join my channel: 👇👇�
🔗 GitHub_Link ❇️ AsyncDepth: Better Monocular 3D Detectors with LiDAR from the Past #LiDAR #Depth #3D Join my channel: 👇👇👇👇👇👇 https://t.me/Artificial_Intelligence_Updates