Model sizes range from 1B to 70B.

Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents.

Releasing open-source large language models (LLMs) presents a dual-use risk since bad actors can easily fine-tune these models for harmful purposes. Even without the open release of weights, weight stealing and fine-tuning APIs make closed models vulnerable to harmful fine-tuning attacks (HFAs).

While training with static demonstrations has shown some promise, we show that such methods fall short for controlling real GUIs due to their failure to deal with real world stochasticity and non-stationarity not captured in static observational data.

A growing collection of pocket-sized gadgets lets you record your meetings and extract value from them. Whether sitting in class, a meeting, or an interview, I've never been fond of taking notes, and I'm far from alone. Not only does the process of scribbling something down cause me to miss what was said immediately after, but I also suffer from awful handwriting, meaning that I can rarely read the notes anyway. Recording interviews has long been a solution, but transcribing interviews is another step (with extra cost) that can leave you with thousands of words of material to sift through, much of it irrelevant. AI notetakers--massively popular at CES 2026 --have emerged to offer a new way of making IRL notetaking easier and faster, putting the power of AI into (or at least adjacent to) a portable device that evokes the microcassette recorder of yesteryear.