As artificial intelligence tools become increasingly capable of generating scientific figures, publishers and researchers are grappling with questions of authenticity, reproducibility, and responsible use.
A new study reveals that initial excitement around in-the-wild robots quickly fades if practical issues and the need for human connection aren’t addressed.
New research demonstrates how robots can infer task completion simply by observing where a person is looking, moving closer to more natural human-robot collaboration.
A new framework demonstrates how to harness the power of artificial intelligence to significantly accelerate research in mathematics and machine learning.
![The system integrates frozen RGB video with trainable event data via a Transformer-based attention mechanism to produce continuous navigation commands [latex] (v, \omega) [/latex], leveraging a fixed RGB backbone to mitigate overfitting during operation in challenging low-light conditions.](https://arxiv.org/html/2603.14397v1/x3.png)
A new framework fuses event-based and traditional vision to enable more robust robot navigation in challenging, low-light indoor environments.
![Through analysis of both planetary and binary star systems, a computational framework successfully rediscovered Kepler’s third law - initially expressed with differing formulations dependent on system mass ratios - and ultimately synthesized these findings into a generalized, unified statement of the universal law of gravitation, [latex]F=f(M,m,T,R)[/latex], demonstrating a pathway for discovering fundamental physical laws from observational data.](https://arxiv.org/html/2603.13727v1/x2.png)
Researchers have developed a new method that mimics how scientists build understanding, progressively revealing underlying physical laws from data.
A new framework empowers robots to replicate human manipulation skills by fusing visual perception with tactile feedback and 3D understanding.
Researchers are exploring how to train artificial intelligence to identify and propose promising research directions, mirroring the intuitive ‘taste’ of experienced scientists.
Researchers have developed a 13-DOF pneumatically actuated upper-body robot and demonstrated a data-driven control strategy that overcomes inherent time delays for smoother, more accurate movements.
Documenting the complex interactions within autonomous AI agents requires a clear, standardized approach, and this paper proposes a practical solution based on established software architecture principles.