GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
InfoWorld

Multi-token prediction technique triples LLM inference speed without auxiliary draft models

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Bringing quantum ideas to the messy world of disordered proteins

Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
IEEE

Comparison of Spelling Error Detection in Turkish Texts With Machine Learning and Transformer-Based Approaches

Abstract: This study aims to compare the performance of five different models for spelling error detection, a crucial task in natural language processing. In this ...
GitHub

bethington/cheat-engine-server-python

This server operates in READ-ONLY mode for safety. It can read and analyze memory but cannot modify it. All operations are logged for security auditing.
IEEE

Development of a Long Short-Term Memory (LSTM)-Based Statistical Model for Earthquake Forecasting in Central Asia

Abstract: Earthquake forecasting using traditional methods remains a complex task due to the inherent nonlinearity and stochastic nature of seismic activity. Therefore, this study examines the ...
blockchain

Google Introduces Sequential Attention to Enhance AI Model Efficiency

According to Richard Seroter, Google Research has unveiled Sequential Attention, a novel mechanism aimed at optimizing AI models by making them leaner and faster without compromising accuracy. This ...