Comparative Analysis of AdPO and Standard RLHF on GSM8K-V Reasoning Accuracy with Clean Images

Abstract

Abstract: In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been significantly improved during both the pre-training and post-training stages. In terms of pre-training, we have scaled the high-quality pre-training datasets from the previous 7 trillion tokens to 18 trillion tokens. This provides a strong foundation for common sense, expert knowledge, and reasoning capabilities. In terms of post-training, we implement intricate supervised finetuning with over 1 million samples, as well

Research Question

Does preference optimization like AdPO maintain GSM8K-V reasoning accuracy on clean images compared to standard RLHF alignment?

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