​ Machine translation, an integral branch of Natural Language Processing, is continually evolving to bridge language gaps across the globe. One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models. Traditional translation models, primarily based on… Read More »This AI Paper from Apple Unveils AlignInstruct: Pioneering Solutions for Unseen Languages and Low-Resource Challenges in Machine Translation Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​ The growing urgency for innovative drugs in various medical fields, such as antibiotics, cancer treatments, autoimmune disorders, and antiviral therapies, underscores the need for increased research and development efforts. Drug discovery, a complex process involving exploring a vast chemical space, can benefit from computational… Read More »Meet MedGAN: A Deep Learning Model based on Wasserstein Generative Adversarial Networks and Graph Convolutional Networks for Novel Molecule Design Sana Hassan Artificial Intelligence Category – MarkTechPost

​ Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 2): Implementing the Neural Structured Learning (NSL) Framework and Building a Data Pipeline Adversarial Learning with NSL CIFAR-10 Dataset Configuring Your Development Environment Need Help Configuring Your Development Environment? Project Structure Configuration File… Read More »Adversarial Learning with Keras and TensorFlow (Part 2): Implementing the Neural Structured Learning (NSL) Framework and Building a Data Pipeline Shivam Chandhok PyImageSearch

​ Transformers have taken over from recurrent neural networks (RNNs) as the preferred architecture for natural language processing (NLP). Transformers stand out conceptually because they directly access each token in a sequence, unlike RNNs that rely on maintaining a recurring state of past inputs. Decoders… Read More »This AI Paper Demonstrates How Decoder-Only Transformers Mimic Infinite Multi-State Recurrent Neural Networks RNNs and Introduces TOVA for Enhanced Efficiency Sana Hassan Artificial Intelligence Category – MarkTechPost

​ Score-based Generative Models (SGMs) are a prominent approach in generative modeling, celebrated for their capacity to produce high-quality samples from intricate, high-dimensional data distributions. This method has garnered empirical success and is bolstered by robust theoretical convergence properties. Notably, it has been established that… Read More »Researchers from the University of Wisconsin-Madison Challenge the Efficacy of Score-based Generative Models: A Surprising Revelation of Gaussian Mimicry in High-Quality Data Generation Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ In understanding choices, there are two main models: normative and descriptive. Normative models explain why people should make certain decisions based on principles, while explanatory models aim to capture how people decide. One recent study claims to have found a more accurate model for… Read More »Decoding Human Risky Choices: Unveiling Dataset Bias in Decision-Making Models Using Machine Learning Niharika Singh Artificial Intelligence Category – MarkTechPost

​ A notable challenge in artificial intelligence has been interpreting and reasoning with tabular data using natural language processing. Unlike traditional text, tables are a more complex medium, rich in structured information that requires a unique approach to comprehension and analysis. This complexity becomes evident… Read More »This AI Paper from UCSD and Google AI Proposes Chain-of-Table Framework: Enhancing the Reasoning Capability of LLMs by Leveraging the Tabular Structure Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ A pressing issue emerges in text-to-image (T2I) generation using reinforcement learning (RL) with quality rewards. Even though potential enhancement in image quality through reinforcement learning RL has been observed, the aggregation of multiple rewards can lead to over-optimization in certain metrics and degradation in… Read More »Meet Parrot: A Novel Multi-Reward Reinforcement Learning RL Framework for Text-to-Image Generation Nikhil Artificial Intelligence Category – MarkTechPost

​ Researchers from Tel-Aviv University and Google Research introduced a new method of user-specific or personalized text-to-image conversion called Prompt-Aligned Personalization (PALP). Generating personalized images from text is a challenging task and requires the presence of diverse elements like specific location, style, or (/and) ambiance.… Read More »Researchers from Google AI and Tel-Aviv University Introduce PALP: A Novel Personalization Method that Allows Better Prompt Alignment of Text-to-Image Models Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​ LLMs have had a significant impact in the fields of code generation and comprehension. These models, trained on extensive code datasets such as GitHub, excel in tasks like text-to-code conversion, code-to-code transpilation, and understanding code. However, many current models merely treat code as sequences… Read More »Researchers from UC Berkeley and Meta Present AST-T5: A Novel Pretraining Paradigm that Harnesses the Power of Abstract Syntax Trees (ASTs) to Boost the Performance of Code-Centric Language Models Sana Hassan Artificial Intelligence Category – MarkTechPost