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cs.CV2026
PACE: Pareto-Adaptive Compression for Efficient Native MLLMs
Lei Tian, Chunzheng Zhu, Kai Wu +2
Native multimodal large language models (native MLLMs) jointly encode visual and linguistic sequences within a unified autoregressive Transformer, emerging as a promising paradigm…
cs.CV2025
BaseReward: A Strong Baseline for Multimodal Reward Model
Yi-Fan Zhang, Haihua Yang, Huanyu Zhang +11
The rapid advancement of Multimodal Large Language Models (MLLMs) has made aligning them with human preferences a critical challenge. Reward Models (RMs) are a core technology for…