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This work identifies a novel phenomenon termed Ambient Context Illusion, where agents fail to execute tasks correctly when non-essential contextual details are omitted, despite unchanged task semantics, and demonstrates that this phenomenon persists in real-world robotic systems, where it can lead to incorrect decision...
Large Vision-Language Models (LVLMs) have achieved remarkable performance across a wide range of tasks; however, they often inherit social biases from their training data, resulting in biased behavior when processing portraits from different social groups. Existing debiasing approaches typically compare token probabili...
This work presents SemPIC, which trains a LoRA-enabled Writer to compile native per-layer document KVs through behavioral distillation while retaining the pretrained decoder as an unchanged Reader, and introduces KV Gradient Checkpointing, which reduces peak training memory without severing gradients through cached KVs...
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