This AI Paper from Arizona State University Discusses Whether Large Language Models (LLMs) Can Reason And Plan?

Practical Solutions for Document Understanding Introducing DocOwl2: A High-Resolution Compression Architecture Understanding multi-page documents and news videos is a common task in human daily life. To address this, Multimodal Large Language Models (MLLMs) need to understand…

Integrating No-Code AI in Non-Technical Higher Education Practical Solutions and Value Recent developments in ML underscore its ability to drive value across diverse sectors. To make ML more accessible to non-STEM students, a case-based approach utilizing…

Introduction GitHub is a vital platform for version control and teamwork. This guide outlines three key GitHub skills: creating and uploading a repository, cloning an existing repository, and writing an effective README file. By following these…

Text-to-video diffusion models have revolutionized media creation and interaction. The lack of a comprehensive dataset of text-to-video prompts in the field has restricted the creative potential and evaluation of these models. VidProM, a pioneering dataset by…

VisionLLaMA, a vision transformer, merges language and vision modalities. It introduces a tailored architecture, VisionLLaMA, to process 2D images effectively. The design retains LLaMA’s architecture and follows ViT’s pipeline, utilizing innovative features. VisionLLaMA achieves superior performance…

OpenAI’s ChatGPT-4 model has been deemed ‘lazy’ by users, sparking concerns about the future of AI. Despite OpenAI’s acknowledgment of the issue and speculation about internal safety mechanisms causing the behavior, the setback presents an opportunity…

Practical Solutions and Value of AI in Mathematical Reasoning Enhancing Mathematical Reasoning Abilities Develop datasets like NuminaMath and Skywork-MathQA with competition-level problems and diverse augmentation techniques. Focus on complicating and diversifying queries with datasets like MuggleMath…

A study compares vision models on non-standard metrics beyond ImageNet. Models like ConvNet and ViT, trained using supervised and CLIP methods, are examined. Different models show varied strengths, which a single statistic cannot fully measure. This…

The research introduces VeRA, a novel method that reduces the number of trainable parameters for language models while maintaining performance levels. By focusing on all linear layers and utilizing quantization techniques and a cleaned dataset, VeRA…

Galileo introduces LLM Studio, a platform that helps developers create trustworthy LLM apps by enabling rapid evaluation, experimentation, and observability. The platform addresses the challenges of holistic evaluation, rapid experimentation, and actionable observability. It offers modules…

Practical Solutions and Value of Edge Pruning for Automated Circuit Finding in Language Models Challenges in Understanding Complex Language Models Understanding inner workings of language models has been challenging due to the increasing complexity of these…

Transforming AI with Generative Solutions Generative AI (Gen AI) is revolutionizing artificial intelligence by enhancing creativity, problem-solving, and automation. However, businesses and developers face challenges when implementing these solutions, particularly due to the lack of compatibility…

This text discusses the use of Large Language Models (LLMs) in the healthcare industry. LLMs, such as GPT-4 and Med-PaLM 2, have shown improved performance in medical tasks and can revolutionize healthcare applications. However, there are…

Researchers from Tel-Aviv University and Google AI introduced Prompt-Aligned Personalization (PALP), enhancing user-specific text-to-image conversion. PALP focuses on personalization and prompt alignment, utilizing Score Distillation Sampling to guide model prediction. It output better text alignment and…