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.
IEEE

Bridging the Modality Gap: Enhancing Channel Prediction with Semantically Aligned LLMs and Knowledge Distillation

Abstract: Accurate channel prediction is essential in massive multiple-input multiple-output (m-MIMO) systems to improve precoding effectiveness and reduce the overhead of channel state information ...
GitHub

Code Structure Analyzer (CSA)

This tool has been developed using both LM Studio and Ollama as LLM providers. The idea behind using a local LLM, like Google's Gemma-3 1B, is data privacy and low cost. In addition, with a good LLM a ...
IEEE

Real-Time Traffic Insights With Physics-Informed Neural Networks: Integrating the Aw-Rascle Model and LLMs

Abstract: Traffic congestion and inefficiencies in transportation networks pose significant challenges to road safety, travel times, and environmental sustainability. Traditional traffic management ...
Computerworld

The AI bubble will burst for firms that can’t get beyond demos and LLMs

Analysts warn that too many companies are ‘chasing the shiny object’ when it comes to AI and forgetting the basics of success. The AI bubble isn’t just hype — it’s real and could create many corporate ...
techxplore

Why AI may overcomplicate answers: Humans and LLMs show 'addition bias,' often choosing extra steps over subtraction

When making decisions and judgments, humans can fall into common "traps," known as cognitive biases. A cognitive bias is essentially the tendency to process information in a specific way or follow a ...