Science Daily

How personalized algorithms trick your brain into wrong answers

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
Psychology Today

Navigating the Impacts of AI-Driven Social Media Algorithms

This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...
IEEE

A Generative Adversarial Network-Based Extractive Text Summarization Using Transductive and Reinforcement Learning

Abstract: Text summarization is crucial in various sectors, such as engineering and healthcare, because it enhances efficiency in terms of time and costs. Current extractive text summarization methods ...
GitHub

RL-FRB/US - (Fiscal Policy Towards Optimizing Macroeconomic Indicators by Integrating FRB/US with Reinforcement Learning)

The RL-FRB/US framework combines the Federal Reserve Board's macroeconomic model (FRB/US) with reinforcement learning techniques to optimize economic policy decisions. This integration, detailed in ...
GitHub

DoctorAgent-RL : Multi-Agent Collaborative Reinforcement Learning for Clinical Dialogue

Through continuous multi-turn interactions between doctor and patient agents, optimized via reinforcement learning, DoctorAgent-RL achieves significant improvements in diagnostic accuracy and ...
IEEE

Run-Length-Limited ISI-Mitigation (RLIM) Coding for Molecular Communication

Abstract: Inter-symbol interference (ISI) limits reliability in diffusion-based molecular communication (MC) channels. We propose RLIM, a family of run-length-limited (RLL) codes that form fixed-size ...