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Meet Hawkeye: A Unified Deep Learning-based Fine-Grained Image Recognition Toolbox Built on PyTorch
In recent years, notable advancements in the design and training of deep learning models have led to significant improvements in image recognition performance, particularly on large-scale datasets. Fine-Grained Image Recognition (FGIR) represents a specialized domain focusing on the detailed recognition of subcategories within broader semantic categories. Despite the progress facilitated by deep learning, FGIR remains…
Meet Graph-Mamba: A Novel Graph Model that Leverages State Space Models SSM for Efficient Data-Dependent Context Selection
Graph Transformers need help with scalability in graph sequence modeling due to high computational costs, and existing attention sparsification methods fail to adequately address data-dependent contexts. State space models (SSMs) like Mamba are effective and efficient in modeling long-range dependencies in sequential data, but adapting them to non-sequential graph data is challenging. Many sequence models…
AI News Weekly – Issue #419: The biggest AI flops of 2024 – Jan 2nd 2025
Powered by aiweekly.co In the News The biggest AI flops of 2024 From chatbots dishing out illegal advice to dodgy AI-generated search results, take a look back over the year’s top AI failures. technologyreview.com Sponsor Discover what the most trusted industry experts are reading Use the Power of AI to access a forward-thinking audience of…
AI News Weekly – Issue #445: – Jun 13th 2025
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Powered by AI Weekly’s future : would you support an ad-free version of this newsletter? typeform.com Welcome AI Weekly’s future : would you support an ad-free version of this newsletter? Dear AI Weekly Readers, After more than five years and over 450 weekly issues, we’re taking a step back to ask an important question: Where…
CMU Research Introduces CoVO-MPC (Covariance-Optimal MPC): A Novel Sampling-based MPC Algorithm that Optimizes the Convergence Rate
Model Predictive Control (MPC) has become a key technology in a number of fields, including power systems, robotics, transportation, and process control. Sampling-based MPC has shown effectiveness in applications such as path planning and control, and it is useful as a subroutine in Model-Based Reinforcement Learning (MBRL), all because of its versatility and parallelizability, Despite…
Enhancing Low-Level Visual Skills in Language Models: Qualcomm AI Research Proposes the Look, Remember, and Reason (LRR) Multi-Modal Language Model
Current multi-modal language models (LMs) face limitations in performing complex visual reasoning tasks. These tasks, such as compositional action recognition in videos, demand an intricate blend of low-level object motion and interaction analysis with high-level causal and compositional spatiotemporal reasoning. While these models excel in various areas, their effectiveness in tasks requiring detailed attention to…
