Researchers from Meta AI and UT Austin Explored Scaling in Auto-Encoders and Introduced ViTok: A ViT-Style Auto-Encoder to Perform Exploration Asif Razzaq Artificial Intelligence Category – MarkTechPost

[[{“value”:” Modern image and video generation methods rely heavily on tokenization to encode high-dimensional data into compact latent representations. While advancements in scaling generator models have been substantial, tokenizers—primarily based on convolutional neural networks (CNNs)—have received comparatively less attention. This raises questions about how scaling… Read More »Researchers from Meta AI and UT Austin Explored Scaling in Auto-Encoders and Introduced ViTok: A ViT-Style Auto-Encoder to Perform Exploration Asif Razzaq Artificial Intelligence Category – MarkTechPost

CHASE: A Query Engine that is Natively Designed to Support Efficient Hybrid Queries on Structured and Unstructured Data Afeerah Naseem Artificial Intelligence Category – MarkTechPost

[[{“value”:” Domains like social media analysis, e-commerce, and healthcare data management require querying through large chunks of structured and unstructured databases. In this modern world, there has been an ever-increasing requirement for the same in many other domains. However, current systems have been proven inefficient… Read More »CHASE: A Query Engine that is Natively Designed to Support Efficient Hybrid Queries on Structured and Unstructured Data Afeerah Naseem Artificial Intelligence Category – MarkTechPost

This paper presents an efficient decoding approach for end-to-end automatic speech recognition (E2E-ASR) with large language models (LLMs). Although shallow fusion is the most common approach to incorporate language models into E2E-ASR decoding, we face two practical problems with LLMs. (1) LLM inference is computationally… Read More »Delayed Fusion: Integrating Large Language Models into First-Pass Decoding in End-to-end Speech Recognition Apple Machine Learning Research

Generating high-quality 3D content requires models capable of learning robust distributions of complex scenes and the real-world objects within them. Recent Gaussian-based 3D reconstruction techniques have achieved impressive results in recovering high-fidelity 3D assets from sparse input images by predicting 3D Gaussians in a feed-forward… Read More »DSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models Apple Machine Learning Research

Large pretrained models are showing increasingly better performance in reasoning and planning tasks across different modalities, opening the possibility to leverage them for complex sequential decision making problems. In this paper, we investigate the capabilities of Large Language Models (LLMs) for reinforcement learning (RL) across… Read More »On the Modeling Capabilities of Large Language Models for Sequential Decision Making Apple Machine Learning Research

[[{“value”:” Chemical reasoning involves intricate, multi-step processes requiring precise calculations, where small errors can lead to significant issues. LLMs often struggle with domain-specific challenges, such as accurately handling chemical formulas, reasoning through complex steps, and integrating code effectively. Despite advancements in scientific reasoning, benchmarks like… Read More »ChemAgent: Enhancing Large Language Models for Complex Chemical Reasoning with Dynamic Memory Frameworks Sana Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:” Multimodal large language models (MLLMs) bridge vision and language, enabling effective interpretation of visual content. However, achieving precise and scalable region-level comprehension for static images and dynamic videos remains challenging. Temporal inconsistencies, scaling inefficiencies, and limited video comprehension hinder progress, particularly in maintaining consistent… Read More »NVIDIA AI Introduces Omni-RGPT: A Unified Multimodal Large Language Model for Seamless Region-level Understanding in Images and Videos Asif Razzaq Artificial Intelligence Category – MarkTechPost

[[{“value”:” Enabling artificial intelligence to navigate and retrieve contextually rich, multi-faceted information from the internet is important in enhancing AI functionalities. Traditional search engines are limited to superficial results, failing to capture the nuances required to investigate profoundly integrated content across a network of related… Read More »This AI Paper from Alibaba Unveils WebWalker: A Multi-Agent Framework for Benchmarking Multistep Reasoning in Web Traversal Aswin Ak Artificial Intelligence Category – MarkTechPost

Machine learning (ML) is now a part of our daily lives, from the voice assistants on our mobiles to advanced robots performing tasks similar to humans. Machine learning (ML) is now a part of our daily lives, from the voice assistants on our mobiles to advanced… Read More »The Roadmap for Mastering Machine Learning in 2025 Kanwal Mehreen MachineLearningMastery.com

[[{“value”:” Large Language Models (LLMs) have become integral to various artificial intelligence applications, demonstrating capabilities in natural language processing, decision-making, and creative tasks. However, critical challenges remain in understanding and predicting their behaviors. Treating LLMs as black boxes complicates efforts to assess their reliability, particularly… Read More »CMU Researchers Propose QueRE: An AI Approach to Extract Useful Features from a LLM Sajjad Ansari Artificial Intelligence Category – MarkTechPost