- Fri. Nov 29th, 2024
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Meet DeepCache: A Simple and Effective Acceleration Algorithm for Dynamically Compressing Diffusion Models during Runtime
Advancements in Artificial Intelligence (AI) and Deep Learning have brought a great transformation in the way humans interact with computers. With the introduction of diffusion models, generative modeling has shown…
This AI Research from The University of Hong Kong and Alibaba Group Unveils ‘LivePhoto’: A Leap Forward in Text-Controlled Video Animation and Motion Intensity Customization
The researchers from The University of Hong Kong, Alibaba Group, and Ant Group developed LivePhoto to solve the issue of temporal motions being overlooked in current text-to-video generation studies. LivePhoto…
Meta AI Presents EfficientSAM: SAM’s Little Brother with 20x Fewer Parameters and 20x Faster Runtime
In vision, the Segment Anything Model (SAM) has achieved remarkable success, attaining cutting-edge results in numerous image segmentation tasks, including zero-shot object proposal generation, zero-shot instance segmentation, and edge detection,…
This AI Research Unveils Alpha-CLIP: Elevating Multimodal Image Analysis with Targeted Attention and Enhanced Control”
How can we improve CLIP for more focused and controlled image understanding and editing? Researchers from Shanghai Jiao Tong University, Fudan University, The Chinese University of Hong Kong, Shanghai AI…
Researchers from MIT and ETH Zurich Developed a Machine-Learning Technique for Enhanced Mixed Integer Linear Programs (MILP) Solving Through Dynamic Separator Selection
Efficiently tackling complex optimization problems, ranging from global package routing to power grid management, has been a persistent challenge. Traditional methods, notably mixed-integer linear programming (MILP) solvers, have been the…
Recent Anthropic Research Tells that You can Increase LLMs Recall Capacity by 70% with a Single Addition to Your Prompt: Unleashing the Power of Claude 2.1 through Strategic Prompting
This research tackles an inherent challenge in Claude 2.1‘s functionality: its reluctance to answer questions based on individual sentences within its extensive 200K token context window. This hesitancy poses a…
This AI Paper from Google and UC Berkeley Introduces NeRFiller: An Artificial Intelligence Approach that Revolutionizes 3D Scene Reconstruction Using 2D Inpainting Diffusion Models
How can missing portions of a 3D capture be effectively completed? This research paper from Google Research and UC Berkeley introduces “NeRFiller,” a novel approach for 3D inpainting, which addresses…
Researchers from AI2 and the University of Washington Uncover the Superficial Nature of Alignment in LLMs and Introduce URIAL: A Novel Tuning-Free Method
Large Language Models (LLMs) are recent innovations in the field of Artificial Intelligence (AI) and Deep Learning. Some of the well-known LLMs, like GPT, PaLM, LLaMa, etc, have demonstrated incredible…
Researchers from MIT and FAIR Meta Unveil RCG (Representation-Conditioned Image Generation): A Groundbreaking AI Framework in Class-Unconditional Image Generation
How can high-quality images be generated without relying on human annotations? This paper from MIT CSAIL and FAIR Meta has addressed the challenge of generating high-quality images without relying on…
Meet Notus: Enhancing Language Models with Data-Driven Fine-Tuning
In the pursuit of refining language models to align more closely with user intent and elevate response quality, a new iteration emerges – Notus. Stemming from Zephyr’s foundations, Notus, a…