What I learned about multi-agent coordination running 9 specialized Claude agents
I've been experimenting with multi-agent AI systems and ended up building something more ambitious than I originally planned: a fully ope...
GPT, Claude, Gemini, and other LLMs
I've been experimenting with multi-agent AI systems and ended up building something more ambitious than I originally planned: a fully ope...
I've been reviewing how various AI memory systems evaluate their performance and noticed a fundamental issue with cross-system comparison...
In the early days of large language models (LLMs), we grew accustomed to massive 10x jumps in reasoning and coding capability with every ...
Hey there, we’re sharing KidGym, an interactive 2D grid-based benchmark for evaluating MLLMs in continuous, trajectory-based interaction,...
Anthropic has updated Claude to perform tasks in its Code and Cowork AI tools autonomously by using your computer for you.
Agile Robots will incorporate Google DeepMind's robotics foundation models into its bots while collecting data for the AI research lab.
For those of you who aren't familiar with SurfSense, SurfSense is an open-source alternative to NotebookLM for teams. It connects any LLM...
After using ChatGPT to help get me more focused and productive in the morning, I used it to do the same thing in the afternoon.
Google CEO Sundar Pichai aims to establish Gemini as the leading AI technology, though specific details on the plan are not available.
Abstract page for arXiv paper 2603.12055: Continual Learning with Vision-Language Models via Semantic-Geometry Preservation
Abstract page for arXiv paper 2602.10273: Power-SMC: Low-Latency Sequence-Level Power Sampling for Training-Free LLM Reasoning
Abstract page for arXiv paper 2602.10218: ACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs
Abstract page for arXiv paper 2602.00004: C$^2$-Cite: Contextual-Aware Citation Generation for Attributed Large Language Models
Abstract page for arXiv paper 2508.08441: SpectraLLM: Uncovering the Ability of LLMs for Molecule Structure Elucidation from Multi-Spectral
Abstract page for arXiv paper 2411.16196: Learn from Foundation Model: Fruit Detection Model without Manual Annotation
Abstract page for arXiv paper 2603.17074: PRISM: Demystifying Retention and Interaction in Mid-Training
Abstract page for arXiv paper 2603.08104: Invisible Safety Threat: Malicious Finetuning for LLM via Steganography
Abstract page for arXiv paper 2602.03773: Reasoning Cache: Continual Improvement Over Long Horizons via Short-Horizon RL
Abstract page for arXiv paper 2601.03385: SIGMA: Scalable Spectral Insights for LLM Model Collapse
Abstract page for arXiv paper 2512.19735: Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting
Abstract page for arXiv paper 2512.10656: Token Sample Complexity of Attention
Abstract page for arXiv paper 2509.24302: LEAF: Language-EEG Aligned Foundation Model for Brain-Computer Interfaces
Abstract page for arXiv paper 2509.21861: SpecMol: A Spectroscopy-Grounded Foundation Model for Multi-Task Molecular Learning
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