most citedMM-RLHF: The Next Step Forward in Multimodal LLM Alignment

1 citations · 2 across the 6 of their papers we have counts for

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cs.CV2025

AdaViP: Aligning Multi-modal LLMs via Adaptive Vision-enhanced Preference Optimization

Jinda Lu, Jinghan Li, Yuan Gao +4

Preference alignment through Direct Preference Optimization (DPO) has demonstrated significant effectiveness in aligning multimodal large language models (MLLMs) with human prefere…

cs.CV2025★ 1 cited

Aligning Multimodal LLM with Human Preference: A Survey

Tao Yu, Yi-Fan Zhang, Chaoyou Fu +14

Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs),…