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cs.CV2024
Token Preference Optimization with Self-Calibrated Visual-Anchored Rewards for Hallucination Mitigation
Jihao Gu, Yingyao Wang, Meng Cao +5
Direct Preference Optimization (DPO) has been demonstrated to be highly effective in mitigating hallucinations in Large Vision Language Models (LVLMs) by aligning their outputs mor…
cs.CL2024
2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision
Shilong Li, Yancheng He, Hui Huang +7
Recent advancements in Direct Preference Optimization (DPO) have significantly enhanced the alignment of Large Language Models (LLMs) with human preferences, owing to its simplicit…