GitHub

Break the Sequential Dependency of LLM Inference Using Lookahead Decoding

Background: Parallel LLM Decoding Using Jacobi Iteration Lookahead decoding is motivated by Jacobi decoding, which views autoregressive decoding as solving nonlinear systems and decodes all future ...
Nature

Machine learning articles from across Nature Portfolio

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
IEEE

Finite Sample Analysis of Open-loop Subspace Identification Methods

Abstract: Subspace identification methods (SIMs) are known for their simple parameterization for MIMO systems and robust numerical properties. However, a comprehensive statistical analysis of SIMs ...
IEEE

A Loop Closing Current Calculation Method for Distribution Networks Considering Load Equivalencing and Optimum Frequency Method

Abstract: Loop closing of distribution network to transfer power has become a common method for load transfer, and the loop closing model of distribution network is the key to loop closing analysis.
GitHub

An autonomous AI agent extension for Antigravity — automates multi-step coding tasks with iterative loop execution, file-based memory, and backpressure validation.

Context decay — LLMs lose track of important details as conversations grow longer. Manual babysitting — Developers must constantly guide the AI, re-prompting after every step.