Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on ...

Overview:  Explore the leading Physical AI development platforms used for robot simulation, reinforcement learning, synthetic ...

An agentic coding tool tasked with cloning and setting up a seemingly benign GitHub repository could execute a malicious ...

Open-source agentic coding model Ornith-1.0, released today under the MIT license, uses a self-improving reinforcement ...

Abstract: Safe reinforcement learning (RL) aims to learn policy while also ensuring the safety constraints. An increasingly common approach is to design a safety filter based on control barrier ...

New research explains why AI models don't just hallucinate randomly but converge on the same invented names repeatedly. The pattern stems from how LLMs ...

EE-RL/ ├─ train.py # Training entry ├─ eval.py # Evaluation entry ├─ config.py # Configuration and algorithm parameters ├─ eval_plots.py # Plotting and summary ├─ utils.py # Utilities ├─ ...

Large language models have moved out of the research lab and into engineers’ daily workflow. LLMs serve as reasoning engines ...

Abstract: In multi-robot systems (MRS) operating across various applications, real-time task allocation and path planning pose significant challenges, often requiring extensive human intervention ...

B, a 3-billion-parameter AI model, is challenging OpenAI, Google and DeepSeek on math and coding benchmarks while reigniting ...

The focus on teaching students how to code—a big emphasis for years—is now expanding to showing them how artificial intelligence works. Code.org, one of the major K-12 computer science education ...

Mechanism-level reproduction of Google's Nested Learning (HOPE) architecture (HOPE blocks, CMS, and Self‑Modifying TITANs), matching the quality bar set by lucidrains' TITAN reference while remaining ...