FBI-LLM (Fully BInarized Large Language Model): An AI Framework Using Autoregressive Distillation for 1-bit Weight Binarization of LLMs from Scratch
Transformer-based LLMs like ChatGPT and LLaMA excel in tasks requiring domain expertise and complex reasoning due to their large parameter sizes and extensive training data. However, their substantial computational and…
Hyperion: A Novel, Modular, Distributed, High-Performance Optimization Framework Targeting both Discrete and Continuous-Time SLAM Applications
In robotics, understanding the position and movement of a sensor suite within its environment is crucial. Traditional methods, called Simultaneous Localization and Mapping (SLAM), often face challenges with unsynchronized sensor…
Enhancing LLM Reliability: The Lookback Lens Approach to Hallucination Detection
Large Language Models (LLMs) like GPT-4 exhibit impressive capabilities in text generation tasks such as summarization and question answering. However, they often produce “hallucinations,” generating content that is factually incorrect…
Korvus: An All-in-One Open-Source RAG (Retrieval-Augmented Generation) Pipeline Built for Postgres
The Retrieval-Augmented Generation (RAG) pipeline includes four major steps— generating embeddings for queries and documents, retrieving relevant documents, analyzing the retrieved data, and generating the final response. Each of these…
Q-GaLore Released: A Memory-Efficient Training Approach for Pre-Training and Fine-Tuning Machine Learning Models
Large Language Models (LLMs) have become critical tools in various domains due to their exceptional ability to understand and generate human language. These models, which often contain billions of parameters,…
A Decade of Transformation: How Deep Learning Redefined Stereo Matching in the Twenties
A fundamental topic in computer vision for nearly half a century, stereo matching involves calculating dense disparity maps from two corrected pictures. It plays a critical role in many applications,…
5 Levels in AI by OpenAI: A Roadmap to Human-Level Problem Solving Capabilities
In an effort to track its advancement towards creating Artificial Intelligence (AI) that can surpass human performance, OpenAI has launched a new classification system. According to a Bloomberg article, OpenAI…
NVIDIA Researchers Introduce MambaVision: A Novel Hybrid Mamba-Transformer Backbone Specifically Tailored for Vision Applications
Computer vision enables machines to interpret & understand visual information from the world. This encompasses a variety of tasks, such as image classification, object detection, and semantic segmentation. Innovations in…
LLaVA-NeXT-Interleave: A Versatile Large Multimodal Model LMM that can Handle Settings like Multi-image, Multi-frame, and Multi-view
Recent progress in Large Multimodal Models (LMMs) has demonstrated remarkable capabilities in various multimodal settings, moving closer to the goal of artificial general intelligence. By using large amounts of vision-language…
InternLM-XComposer-2.5 (IXC-2.5): A Versatile Large-Vision Language Model that Supports Long-Contextual Input and Output
Large Language Models (LLMs) have made significant strides in recent years, prompting researchers to explore the development of Large Vision Language Models (LVLMs). These models aim to integrate visual and…