XINLI1997/ReMaRk-Qwen3.5-9B-RedditV2-RankGRPO-s42
ReMaRk-Qwen3.5-9B-RedditV2-RankGRPO-s42 by XINLI1997 is a 9 billion parameter language model, based on Qwen3.5-9B-Base, specifically fine-tuned for conversational movie recommendations. It utilizes the Rank-GRPO objective on the Reddit-v2 dataset, focusing on removing responder noise for LLM recommenders. This model excels at generating movie recommendations based on user preferences, providing a specialized solution for recommendation systems rather than general conversational AI.
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Overview
XINLI1997/ReMaRk-Qwen3.5-9B-RedditV2-RankGRPO-s42 is a 9 billion parameter language model, built upon the Qwen3.5-9B-Base architecture, specifically optimized for conversational movie recommendations. This model implements the Rank-GRPO objective, as detailed in the paper "Many Right Answers, One Training Example: Removing Responder Noise from GRPO for LLM Recommenders" (arXiv: 2610.17771). It was trained using reinforcement learning on the Reddit-v2 dataset, which focuses on movie recommendations, to enhance its ability to provide relevant suggestions while mitigating noise from community responses.
Key Capabilities
- Specialized Recommendation: Designed to generate movie recommendations based on user input, such as liked films.
- Noise Reduction: Incorporates the Rank-GRPO objective to improve recommendation quality by addressing responder noise in training data.
- Conversational Interface: Capable of understanding and responding to natural language queries for movie suggestions.
Good For
- Building Movie Recommender Systems: Ideal for applications requiring a dedicated LLM for movie suggestions.
- Research in Recommendation Systems: Useful for researchers exploring GRPO-based methods and noise reduction in LLM recommenders.
Limitations
- Domain Specificity: Primarily trained for movie recommendations and not suitable as a general-purpose assistant.
- Bias Reflection: Recommendations may reflect biases present in the Reddit community data and favor popular items.
- Language Support: Currently supports English only.