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CED reveals that VLMs can be trained to prioritize evidence-based reasoning over language shortcuts, leading to more reliable visual understanding.
SPOT-E transforms frozen VLMs into more reliable evidence readers by dynamically spotlighting critical visual information during inference.
The landscape of deep learning optimizers is vast, but this paper cuts through the noise to reveal the fundamental trade-offs and promising future directions for efficient, robust, and trustworthy training.
