Revolutionizing 3D Scene Modeling with Generalized Exponential Splatting

Learn how to create Clarifai Workflows using Python SDK and YAML configurations in this tutorial.

Practical Solutions and Value of Phi Silica: A 3.3 Billion Parameter AI Model Model Size and Efficiency Phi Silica is the smallest model in the Phi family, offering high performance with minimal resource usage on CPUs…

The Efficient Deployment of Large Language Models (LLMs) Practical Solutions and Value The efficient deployment of large language models (LLMs) requires high throughput and low latency. However, the substantial memory consumption of the key-value (KV) cache…

Understanding Model Inversion Attacks Model Inversion (MI) attacks are privacy threats targeting machine learning models. Attackers aim to reverse-engineer the model’s outputs to reveal sensitive training data, including private images, health information, financial details, and personal…

Researchers released MediTron, an open-source medical LLM suite with 7B and 70B parameter variants, excelling in benchmarks and tailored for tasks like medical QA. It uses an extensive medical dataset for training but requires further testing…

The {dplyr} package in R is designed for data manipulation, offering functions to filter, sort, and summarize data. One can group data, count distinct values, and strategically create or modify variables with “if else” or “case…

Modeling Collaborator introduces a user-in-the-loop framework to transform visual concepts into vision models, addressing the need for user-centric training. By leveraging human cognitive processes and advancements in language and vision models, it simplifies the definition and…

The Challenge in Multilingual NLP The increasing availability of digital text in diverse languages and scripts presents a significant challenge for natural language processing (NLP). Multilingual pre-trained language models (mPLMs) often struggle to handle transliterated data…

Phase-Field Models and Their Importance Phase-field models are essential for simulating material behavior by connecting atomic-level details to larger-scale effects. They help in understanding microstructural changes and phase transformations, which are important in various processes like…

This article discusses the concept of the adaptive linear neuron classifier, also known as adaline. Adaline is a binary classifier that uses a linear activation function for learning weights and a step function for making predictions.…

Practical Solutions and Value of Img-Diff Dataset Enhancing Multimodal Language Models Multimodal Language Models (MLLMs) have evolved to improve text-image interactions through various techniques. Models like Flamingo, IDEFICS, BLIP-2, and Qwen-VL use learnable queries, while LLaVA…

This text discusses the limitations of large language models (LLMs) in terms of semantic understanding and logical reasoning. To address these limitations, the AI community has turned to retrieval augmented generative (RAG) frameworks, which leverage knowledge…