​ 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 potential in generating content. From question answering and text summarization to language translation and… Read More »Researchers from AI2 and the University of Washington Uncover the Superficial Nature of Alignment in LLMs and Introduce URIAL: A Novel Tuning-Free Method Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ 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 significant hurdle in maximizing the model’s recall capacity, prompting the exploration of a solution.… Read More »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 Madhur Garg Artificial Intelligence Category – MarkTechPost

​ 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 the challenge of reconstructing incomplete 3D scenes or objects often missing due to reconstruction… Read More »This AI Paper from Google and UC Berkeley Introduces NeRFiller: An Artificial Intelligence Approach that Revolutionizes 3D Scene Reconstruction Using 2D Inpainting Diffusion Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​ How can high-quality 3D reconstructions be achieved from a limited number of images? A team of researchers from Columbia University and Google introduced ‘ReconFusion,’ An artificial intelligence method that solves the problem of limited input views when reconstructing 3D scenes from images. It addresses… Read More »Columbia and Google Researchers Introduce ‘ReconFusion’: An Artificial Intelligence Method for Efficient 3D Reconstruction with Minimal Images Sana Hassan Artificial Intelligence Category – MarkTechPost

​ 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 human annotations. They have introduced a novel framework called Representation-Conditioned Image Generation (RCG) that… Read More »Researchers from MIT and FAIR Meta Unveil RCG (Representation-Conditioned Image Generation): A Groundbreaking AI Framework in Class-Unconditional Image Generation Sana Hassan Artificial Intelligence Category – MarkTechPost

​ 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 fine-tuned version of Data Preference Optimization (DPO), emphasizes high-quality data curation for a more… Read More »Meet Notus: Enhancing Language Models with Data-Driven Fine-Tuning Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Over the past few years, there have been significant advancements in Machine Learning (ML), with numerous frameworks and libraries developed to simplify our tasks. Among these innovations, Apple recently launched a new framework, MLX, designed specifically for Apple silicon, that facilitates the training and… Read More »Apple AI Research Releases MLX: An Efficient Machine Learning Framework Specifically Designed for Apple Silicon Asif Razzaq Artificial Intelligence Category – MarkTechPost

​ Researchers from FNii CUHKSZ, SSE CUHKSZ introduce MVHumanNet, a vast dataset for multi-view human action sequences with extensive annotations, including human masks, camera parameters, 2D and 3D key points, SMPL/SMPLX parameters, and textual descriptions. MVHumanNet facilitates exploration in action recognition, human NeRF reconstruction, text-driven… Read More »Meet MVHumanNet: A Large-Scale Dataset that Comprises Multi-View Human Action Sequences of 4,500 Human Identities Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ The team of researchers from Google developed a new fine-tuning strategy to address the challenge of generating correct answers using LLMs. The strategy, called chain-of-thought (CoT) fine-tuning, optimizes the average log-likelihood of correct answers and aims to maximize the marginal log-likelihood of generating accurate… Read More »Google AI Research Proposes TRICE: A New Machine Learning Algorithm for Tuning LLMs to be Better at Solving Question-Answering Tasks Using Chain-of-Thought (CoT) Prompting Adnan Hassan Artificial Intelligence Category – MarkTechPost