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This AI Paper Introduces an LLM+FOON Framework: A Graph-Validated Approach for Robotic Cooking Task Planning from Video Instructions

RoboticsMay 2, 2025124Views0Likes0Comments
Robots are increasingly being developed for home environments, specifically to enable them to perform daily activities like cooking. These tasks involve a combination of visual interpretation, manipulation, and decision-making across a series of actions. Cooking, in particular, is complex for robots due to the diversity in utensils, varying visual perspectives, and frequent omissions of intermediate…

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Meta AI Introduces Token-Shuffle: A Simple AI Approach to Reducing Image Tokens in Transformers

AI NewsApril 27, 2025112Views0Likes0Comments
Autoregressive (AR) models have made significant advances in language generation and are increasingly explored for image synthesis. However, scaling AR models to high-resolution images remains a persistent challenge. Unlike text, where relatively few tokens are required, high-resolution images necessitate thousands of tokens, leading to quadratic growth in computational cost. As a result, most AR-based multimodal…

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Researchers at Physical Intelligence Introduce π-0.5: A New AI Framework for Real-Time Adaptive Intelligence in Physical Systems

RoboticsApril 27, 2025211Views0Likes0Comments
Designing intelligent systems that function reliably in dynamic physical environments remains one of the more difficult frontiers in AI. While significant advances have been made in perception and planning within simulated or controlled contexts, the real world is noisy, unpredictable, and resistant to abstraction. Traditional AI systems often rely on high-level representations detached from their…

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Long-Context Multimodal Understanding No Longer Requires Massive Models: NVIDIA AI Introduces Eagle 2.5, a Generalist Vision-Language Model that Matches GPT-4o on Video Tasks Using Just 8B Parameters

AI NewsApril 22, 2025105Views0Likes0Comments
In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation remains: the inability to effectively process long-context multimodal data such as high-resolution imagery or extended video sequences. Many existing VLMs are optimized for short-context scenarios and struggle with performance degradation, inefficient memory usage, or loss…

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