Unlocking precise 3D object localization without 3D data, VLM-Grounder revolutionizes visual grounding by leveraging advanced 2D image analysis—achieving breakthrough accuracy and redefining zero-shot ...

Researchers developed a scalable framework for data attribution in diffusion models, using influence functions to improve model transparency and accountability. OpenAI researchers propose TrigFlow, a ...

*Important notice: arXiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as definitive, used to guide development decisions, or treated as ...

Researchers introduce iDP3, a 3D visuomotor policy that enables humanoid robots to perform complex tasks autonomously in diverse real-world environments using lab-collected data.

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A groundbreaking AI model, CoTracker3, dramatically improves video point tracking by eliminating complex components and effectively leveraging real-world data, outpacing existing technologies with ...

Despite their impressive performance, Apple’s research reveals that large language models still struggle with true mathematical reasoning, relying on pattern-matching instead of formal logic - a ...

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*Important notice: arXiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as definitive, used to guide development decisions, or treated as ...

*Important notice: arXiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as definitive, used to guide development decisions, or treated as ...

A groundbreaking framework uses influence functions to trace how training data impacts AI-generated outputs, ensuring greater transparency and trust in diffusion models applied across industries.

Researchers from Anthropic explore AI's potential to secretly influence and manipulate decisions, highlighting the urgency for new evaluation strategies as AI capabilities advance. In a recent ...