Models, methods, and the machinery of intelligence.
arXiv
Verdict: NotableArtificial general intelligence (AGI) requires a method that can understand, generate, reason, and act across diverse domains and modalities.
Rapid advances in cowork agents are shifting human-AI collaboration toward real-world automation, delivering software, designs, and other artifacts.
General-purpose robot policies must work across robots, tasks, and environments, yet the variation that makes physical trials informative also makes them difficult to reproduce.
Large language models are deployed as long-horizon agents that compose diverse tools across MCP services into executable workflows.
Traditional image cropping assumes the photograph already contains the composition worth keeping, and asks only where to crop.
Speculative decoding accelerates memory-bound LLM decoding with a lightweight drafter, and parallel drafters extend this speedup by drafting a whole block in one forward pass.
GUI web agents require realistic and interactive environments that remain stable during both evaluation and training.
Progress in AI is often measured by what a single model can do on its own.
Complex documents such as scientific papers contain rich information in tables, figures, and equations; however, existing deep research (DR) agents typically reduce papers to ....