IEEE

Reinforcement Learning-powered Effectiveness and Efficiency Few-shot Jailbreaking Attack LLMs

Abstract: The widespread use of large language models (LLMs) has brought about security risks, including biases, discrimination, and ethical concerns. Reinforcement Learning from Human Feedback (RLHF) ...
GitHub

Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning

Welcome to the official codebase for Franca (pronounced Fran-ka), the first fully open-source vision foundation model—including data, code, and pretrained weights. Franca matches or surpasses the ...
GitHub

Pioneering Perception Policy with Reinforcement Learning

We present Perception-R1, a scalable RL framework using Group Relative Policy Optimization (GRPO) during MLLM post-training. Key innovations: 🎯 Perceptual Perplexity Analysis: We introduce a novel ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
IEEE

Deep Reinforcement Learning Based Bit Flipping Algorithm for Hamming Codes

Abstract: Hamming codes are effective for single-bit error correction but struggle with multiple-bit errors. While the bit-flipping (BF) algorithm can handle some ...