Large language models store substantial factual knowledge in their parameters, yet this knowledge is difficult to control, update, and reliably elicit at inference time. Existing memory-augmented approaches typically rely on a single auxiliary mechanism, such as retrieval, parameter updates, or neural memory, and there...
Yifan Lu, Ru-Bin Wei, Zi-Yun Zou et al.· 0 citations
Experiments on the SLAKE and MIMIC-CXR datasets demonstrate that CAST consistently outperforms strong baselines and surpasses decoding strategies reliant on ground truth, and indicates that compact, automatically selected regions provide highly effective contrastive guidance without expert annotations.
Yifan Lu, A. Dukre, Abhijit Das et al.· 0 citations
This work investigates two representative model families, LLaVA-1.5 and Qwen2.5, and provides a token-, layer-, and head-level account of how VLMs transform object grounding into spatial relations, showing that knowing where objects are is not equivalent to knowing how they relate.
Xi-Wei Liu, Yu-Long Li, Xin-Lin Zhuang et al.· 1 citation
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