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WorldVLA: Towards Autoregressive Action World Model

arxiv.org/abs/2506.21539

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arXiv.orgWorldVLA: Towards Autoregressive Action World ModelWe present WorldVLA, an autoregressive action world model that unifies action and image understanding and generation. Our WorldVLA intergrates Vision-Language-Action (VLA) model and world model in one single framework. The world model predicts future images by leveraging both action and image understanding, with the purpose of learning the underlying physics of the environment to improve action generation. Meanwhile, the action model generates the subsequent actions based on image observations, aiding in visual understanding and in turn helps visual generation of the world model. We demonstrate that WorldVLA outperforms standalone action and world models, highlighting the mutual enhancement between the world model and the action model. In addition, we find that the performance of the action model deteriorates when generating sequences of actions in an autoregressive manner. This phenomenon can be attributed to the model's limited generalization capability for action prediction, leading to the propagation of errors from earlier actions to subsequent ones. To address this issue, we propose an attention mask strategy that selectively masks prior actions during the generation of the current action, which shows significant performance improvement in the action chunk generation task.
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The #law also refers to other elements that can’t be attributed to a #machine, Millet said, when it requires an #author’s “signature” to transfer, talks about co-authors’ “intention,” & refers to an author’s “nationality or domicile.”

“Machines do not have property, traditional human lifespans, family members, domiciles, nationalities, mentes reae, or signatures,” Millet said, later adding that “the #Copyright Act makes no sense if an ‘author’ is not a human being.”

arXiv.orgEnhancing Frame Detection with Retrieval Augmented GenerationRecent advancements in Natural Language Processing have significantly improved the extraction of structured semantic representations from unstructured text, especially through Frame Semantic Role Labeling (FSRL). Despite this progress, the potential of Retrieval-Augmented Generation (RAG) models for frame detection remains under-explored. In this paper, we present the first RAG-based approach for frame detection called RCIF (Retrieve Candidates and Identify Frames). RCIF is also the first approach to operate without the need for explicit target span and comprises three main stages: (1) generation of frame embeddings from various representations ; (2) retrieval of candidate frames given an input text; and (3) identification of the most suitable frames. We conducted extensive experiments across multiple configurations, including zero-shot, few-shot, and fine-tuning settings. Our results show that our retrieval component significantly reduces the complexity of the task by narrowing the search space thus allowing the frame identifier to refine and complete the set of candidates. Our approach achieves state-of-the-art performance on FrameNet 1.5 and 1.7, demonstrating its robustness in scenarios where only raw text is provided. Furthermore, we leverage the structured representation obtained through this method as a proxy to enhance generalization across lexical variations in the task of translating natural language questions into SPARQL queries.
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Ejijah McCoy found work as a fireman and oiler at the #Michigan Central #Railroad, fueling and maintaining #trains. (That hashtag is for all the #train fans on Fedi. You're welcome.)

While working on Trains, he quickly recognized flaws in the systems for keeping them oiled, which required frequent stops for maintenance, and began developing improvements. Around 1870, he started his own #manufacturing #business for #B2B #machine parts.

In 1872, he patented an automatic oiling known as the "McCoy Lubricating Cup", which at the time was a major step forward in quality and efficiency, drastically cutting down work for #engineers. Other #companies had made such devices before, and attempted to make something to compete, but his design was simply so good that companies would ask for it by name.

This is the origin of the phrase, "The Real McCoy".

In this modern era, it is important to remember the contributions of people like McCoy, and the detriment of policies which held them back.

4-min clip from the 1997 Robert Zemeckis #film 'Contact' based on the 1985 #novel by Carl Sagan.

Dr. Ellie Arroway (Jody Foster) enters the great #gyroscopic #SpaceTime #machine, opening up a #wormhole #portal. #Gyroscope devices have factored heavily in #SciFi #movies & #books, going all the way back to #HGWells & #AlfredJarry, pre-1900.

🔗 youtube.com/watch?v=scBY3cVyey
🔗 Wikipedia.org/wiki/Contact_(19