InfoWorld

AI-augmented data quality engineering

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

TTT-Discover optimizes GPU kernels 2x faster than human experts — by training during inference

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

Reinforcement learning session gathers experts

An intensive programme on reinforcement learning, brought together 60 international participants including students, ...
Tech Xplore

Why reinforcement learning breaks at scale, and how a new method fixes it

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
GitHub

Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning

REC-R1 is a general framework that bridges generative large language models (LLMs) and recommendation systems via reinforcement learning. Check the paper here.
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
IEEE

Empathy Level Alignment via Reinforcement Learning for Empathetic Response Generation

Abstract: Empathetic response generation, aiming to understand the user’s situation and feelings and respond empathically, is crucial in building human-like dialogue systems. Traditional approaches ...
IEEE

Curricular Subgoals for Inverse Reinforcement Learning

Abstract: Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success in ...