86 citations · 170 across the 21 of their papers we have counts for
4 papers · 1 filter
PEA-DPO: Perception-Enhanced Alignment Direct Preference Optimization for MLLMs Alignment
Jiawei Feng, Jiancan Wu, Xingyu Zhu +3
Direct Preference Optimization (DPO) has emerged as an effective approach for aligning large language models (LLMs) with human preferences. However, its adaptation to multimodal se…
Beyond Where to Look: Trajectory-Guided Reinforcement Learning for Multimodal RLVR
Jinda Lu, Junkang Wu, Jinghan Li +6
Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) for multimodal large language models (MLLMs) have mainly focused on improving final answer correctness and…
Bridging Perception and Reasoning: Token Reweighting for RLVR in Multimodal LLMs
Jinda Lu, Junkang Wu, Jinghan Li +6
Extending Reinforcement Learning with Verifiable Rewards (RLVR) to multimodal large language models (MLLMs) faces a fundamental challenge: their responses inherently interleave per…
DAMA: Data- and Model-aware Alignment of Multi-modal LLMs
Jinda Lu, Junkang Wu, Jinghan Li +6
Direct Preference Optimization (DPO) has shown effectiveness in aligning multi-modal large language models (MLLM) with human preferences. However, existing methods exhibit an imbal…