Training LLMs and VLMs through reinforcement learning delivers better results than using hand-crafted examples.

This repository contains the source code for reproducing the CD-RLHF. We implement CD-RLHF based on DeepSpeed-Chat. We conduct experiments on two datasets: OpenAI TL;DR, and UltraFeedback. We split ...

We provide the 9 models evaluated in the MetaAligner paper as follows. Note that though all models are fine-tuned on certain objectives, you can always extend their capability to unseen objectives by ...

However, EEG data have a complex nonEuclidean structure and are often scarce, making training effective graph neural network (GNN) models difficult. We propose a “pre-train, prompt” framework in graph ...

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Qwen AI aims to address these challenges with Qwen2.5-Max, a large MoE model pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning ...