metadata
language:
- en
license: apache-2.0
datasets:
- qingfei1/R-Search_datasets
task_categories:
- question-answering
library_name:
- datasets
R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement Learning
🤗 [R-Search Datasets] • 💻 [Github Repo]
R-Search is a novel reinforcement learning framework for reasoning–search integration. It enables LLMs to autonomously perform multi-step reasoning with deep search interaction, and to learn optimal reasoning–search trajectories via multi-reward signals, substantially improving performance on complex logic- and knowledge-intensive tasks.
Trained Models
We open-sourced the following models trained only on the 2wikimultihopqa training set:
| Model | Huggingface Repo | Description |
|---|---|---|
| R-Search-7b-grpo | 🤗 Huggingface Repo | Trained Qwen2.5-7B-Instruct using the GRPO algorithm |
| R-Search-3b-grpo | 🤗 Huggingface Repo | Trained Qwen2.5-3B-Instruct using the GRPO algorithm |
| R-Search-7b-ppo | 🤗 Huggingface Repo | Trained Qwen2.5-7B-Instruct using the PPO algorithm |
| R-Search-3b-ppo | 🤗 Huggingface Repo | Trained Qwen2.5-3B-Instruct using the PPO algorithm |