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cs.CL2026
KA2L: A Knowledge-Aware Active Learning Framework for LLMs
Haoxuan Yin, Chen Tang, Yangfan Wang +2
Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a paucity of research on the depth o…
cs.CL2025
The Mirage of Performance Gains: Why Contrastive Decoding Fails to Mitigate Object Hallucinations in MLLMs?
Hao Yin, Guangzong Si, Zilei Wang
Contrastive decoding strategies are widely used to reduce object hallucinations in multimodal large language models (MLLMs). These methods work by constructing contrastive samples…