Science – Page 147

Charting a Faster Course: Multi-Graph Search for Robot Navigation

14.02.2026 by ebaster

The system generates navigable environments represented as occupancy grids-used to compute attractive forces during path planning-and successfully demonstrates its capabilities beyond robotic manipulation by autonomously charting a course through a complex three-dimensional space.

A new motion planning framework dramatically improves efficiency by simultaneously exploring multiple potential paths for robots operating in complex, high-dimensional spaces.

Unlocking Plasma Physics Knowledge with AI

14.02.2026 by ebaster

The annotated dataset reveals a nuanced approach to entity recognition, where terms are intentionally layered with multiple, overlapping classifications to reflect the inherent complexity of information.

A new approach to information extraction leverages artificial intelligence to identify and categorize key concepts within complex research articles.

Building Robots That Understand the World: LDA-1B Learns From Experience

14.02.2026 by ebaster

Latent Dirichlet Allocation (LDA) demonstrates scalable performance in action prediction, achieving 6.6 error with 30,000 hours of training-a result attributable to effective data diversification-and consistently surpasses the Unsupervised Weighting Model (UWM) across parameter scales-from 0.1 to 1 billion-while the baseline method rapidly plateaus in its learning capacity.

A new foundation model, LDA-1B, is pushing the boundaries of embodied AI by learning robust interaction dynamics from a vast and diverse range of real-world robot data.

Beyond Fact-Checking: How Humans and AI Can Reason Together

14.02.2026 by ebaster

A new system called Althea demonstrates that collaborative exploration, rather than simple AI assistance, is key to improving critical thinking and building trust in information.

Building Smarter AI Agents: A System for Adaptive Configuration

14.02.2026 by ebaster

The method navigates a vast configuration space-spanning thousands of possibilities-to optimize performance for the Qwen 2.5 7B Instruct model across multiple datasets, demonstrating a capacity to adapt and improve beyond baseline results.

New research details a framework for automatically optimizing the workflows and instructions of AI agents powered by large language models.

The AI Negotiation Edge: Control vs. Collective Gain

14.02.2026 by ebaster

Delegate agents demonstrably improve trade outcomes by consistently proposing offers that yield a significant increase in receiver surplus-a statistically significant shift not observed in non-AI-assisted scenarios [latex] (p<0.01) [/latex], suggesting a capacity for mutually beneficial negotiation.

New research explores how different levels of AI involvement in multi-party bargaining – from advice to full delegation – impacts strategic choices and overall outcomes.

Bridging the AI Gap for Language Professionals

14.02.2026 by ebaster

Jupyter notebooks facilitate the didactic exploration of complex neural network processes, as demonstrated by the visualization of both embedding transformations within hidden layers and the detailed examination of self-attention mechanisms in transformer language models.

A new technical curriculum aims to equip translators and communicators with the skills needed to navigate the rapidly evolving landscape of language-oriented artificial intelligence.

Robots Learn by Building Their Own Worlds

14.02.2026 by ebaster

Complex long-horizon tasks are systematically decomposed into interconnected simple tasks, establishing a framework where inter-task edges facilitate transitions between distinct object manipulations or resets of temporal states, thereby enabling solutions to problems requiring extended sequential reasoning.

Researchers have developed a system that allows robots to generate increasingly complex environments and tasks, enabling more robust learning for long-horizon challenges.

The Kitsch Machine: When AI Art Goes Wrong

14.02.2026 by ebaster

Generative AI is flooding the art world with images, but a critical look reveals a troubling tendency towards superficiality and the normalization of kitsch.

Robots Learn Spatial Reasoning from Diffusion Models

14.02.2026 by ebaster

Researchers have developed a new framework that imbues robots with improved geometric understanding by distilling knowledge from powerful diffusion models.