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This AI Paper from Aalto University Introduces VQ-VFM-OCL: A Quantization-Based Vision Foundation Model for Object-Centric Learning Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Object-centric learning (OCL) is an area of computer vision that aims to decompose visual scenes into distinct objects, enabling advanced vision tasks such as prediction, reasoning, and decision-making. Traditional methods in visual recognition often rely on feature extraction without explicitly segmenting objects, which limits… Read More »This AI Paper from Aalto University Introduces VQ-VFM-OCL: A Quantization-Based Vision Foundation Model for Object-Centric Learning Nikhil Artificial Intelligence Category – MarkTechPost

Few-Shot Preference Optimization (FSPO): A Novel Machine Learning Framework Designed to Model Diverse Sub-Populations in Preference Datasets to Elicit Personalization in Language Models for Open-Ended Question Answering Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Personalizing LLMs is essential for applications such as virtual assistants and content recommendations, ensuring responses align with individual user preferences. Unlike traditional approaches that optimize models based on aggregated user feedback, personalization aims to capture the diversity of individual perspectives shaped by culture, experiences,… Read More »Few-Shot Preference Optimization (FSPO): A Novel Machine Learning Framework Designed to Model Diverse Sub-Populations in Preference Datasets to Elicit Personalization in Language Models for Open-Ended Question Answering Sana Hassan Artificial Intelligence Category – MarkTechPost

Speaker-IPL: Unsupervised Learning of Speaker Characteristics with i-Vector Based Pseudo-Labels Apple Machine Learning Research

​Iterative self-training, or iterative pseudo-labeling (IPL) — using an improved model from the current iteration to provide pseudo-labels for the next iteration — has proven to be a powerful approach to enhance the quality of speaker representations. Recent applications of IPL in unsupervised speaker recognition… Read More »Speaker-IPL: Unsupervised Learning of Speaker Characteristics with i-Vector Based Pseudo-Labels Apple Machine Learning Research

M2R2: Mixture of Multi-Rate Residuals for Efficient Transformer Inference Apple Machine Learning Research

​Residual transformations enhance the representational depth and expressive power of large language models (LLMs). However, applying static residual transformations across all tokens in auto-regressive generation leads to a suboptimal trade-off between inference efficiency and generation fidelity. Existing methods, including Early Exiting, Skip Decoding, and Mixture-of-Depth… Read More »M2R2: Mixture of Multi-Rate Residuals for Efficient Transformer Inference Apple Machine Learning Research

SELMA: A Speech-Enabled Language Model for Virtual Assistant Interactions Apple Machine Learning Research

​In this work, we present and evaluate SELMA, a Speech-Enabled Language Model for virtual Assistant interactions that integrates audio and text as inputs to a Large Language Model (LLM). SELMA is designed to handle three primary and two auxiliary tasks related to interactions with virtual… Read More »SELMA: A Speech-Enabled Language Model for Virtual Assistant Interactions Apple Machine Learning Research

Does Spatial Cognition Emerge in Frontier Models? Apple Machine Learning Research

​Not yet. We present SPACE, a benchmark that systematically evaluates spatial cognition in frontier models. Our benchmark builds on decades of research in cognitive science. It evaluates large-scale mapping abilities that are brought to bear when an organism traverses physical environments, smaller-scale reasoning about object… Read More »Does Spatial Cognition Emerge in Frontier Models? Apple Machine Learning Research

Towards Automatic Assessment of Self-Supervised Speech Models Using Rank Apple Machine Learning Research

​This study explores using embedding rank as an unsupervised evaluation metric for general-purpose speech encoders trained via self-supervised learning (SSL). Traditionally, assessing the performance of these encoders is resource-intensive and requires labeled data from the downstream tasks. Inspired by the vision domain, where embedding rank… Read More »Towards Automatic Assessment of Self-Supervised Speech Models Using Rank Apple Machine Learning Research

Project Alexandria: Democratizing Scientific Knowledge Through Structured Fact Extraction with LLMs Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Scientific publishing has expanded significantly in recent decades, yet access to crucial research remains restricted for many, particularly in developing countries, independent researchers, and small academic institutions. The rising costs of journal subscriptions exacerbate this disparity, limiting the availability of knowledge even in well-funded… Read More »Project Alexandria: Democratizing Scientific Knowledge Through Structured Fact Extraction with LLMs Vineet Kumar Artificial Intelligence Category – MarkTechPost

This AI Paper Identifies Function Vector Heads as Key Drivers of In-Context Learning in Large Language Models Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In-context learning (ICL) is something that allows large language models (LLMs) to generalize & adapt to new tasks with minimal demonstrations. ICL is crucial for improving model flexibility, efficiency, and application in language translation, text summarization, and automated reasoning. Despite its significance, the exact… Read More »This AI Paper Identifies Function Vector Heads as Key Drivers of In-Context Learning in Large Language Models Nikhil Artificial Intelligence Category – MarkTechPost

Accelerate AWS Well-Architected reviews with Generative AI Shoeb Bustani AWS Machine Learning Blog

​[[{“value”:” Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more… Read More »Accelerate AWS Well-Architected reviews with Generative AI Shoeb Bustani AWS Machine Learning Blog