Browsing: AI & Machine Learning

TL;DR: A group of researchers from Stanford College, SambaNova Methods and UC Berkeley introduce ACE framework that improves LLM efficiency…

Google has open-sourced a Mannequin Context Protocol (MCP) server that exposes read-only entry to the Google Advertisements API for agentic…

TL;DR: Laptop-use brokers are VLM-driven UI brokers that act like customers on unmodified software program. Baselines on OSWorld began at…

TL;DR: Skala is a deep-learning change–correlation practical for Kohn–Sham Density Useful Concept (DFT) that targets hybrid-level accuracy at semi-local price,…

Can an iterative draft–revise solver that repeatedly updates a latent scratchpad outperform far bigger autoregressive LLMs on ARC-AGI? Samsung SAIT…

To realize this at scale, textual content annotation instruments, geared up with options resembling collaborative workflows, automated pre-labeling, and high…

TL;DR: A brand new analysis from Apple, formalizes what “mid-training” ought to do earlier than reinforcement studying RL post-training and…

TL;DR: AgentFlow is a trainable agent framework with 4 modules—Planner, Executor, Verifier, Generator—coordinated by an specific reminiscence and toolset. The…

How do you audit frontier LLMs for misaligned conduct in real looking multi-turn, tool-use settings—at scale and past coarse mixture…

MCP (Mannequin Context Protocol): Open, transport-agnostic protocol that standardizes discovery and invocation of instruments/sources throughout…