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Medical VQA models can now reason more reliably thanks to a new framework that disentangles true causal effects from spurious correlations by jointly tackling observable and unobservable confounders.
Ditch the polarity labels: SemEval-2026's DimABSA task reveals how modeling sentiment along valence-arousal dimensions unlocks nuanced understanding in both aspect-based sentiment analysis and stance detection.
Swap out slow, one-token-at-a-time generation in VLMs for a 6x speed boost, without sacrificing quality, using a surprisingly simple direct conversion to block-diffusion decoding.
