7 accepted papers
Real-world multimodal systems inevitably face partial observability due to sensor dropout and degradation. Standard robustness methods can improve average performance, but they often remain unreliable in rare, adverse long-tail conditions. Under a locked same-support contract, we uncover a same-supp…
Self-attention with separate pre- and post-projections can be a universal approximator (on compact domains) under mild conditions. Yet we observe a striking gap: an attention-only Transformer (w/o FFN layers) exhibits a marked accuracy drop relative to its standard interleaved attention--FFN baselin
Neural networks necessitate nonlinearities to achieve universal approximability. Traditional activation functions introduce nonlinearities through rigid feature rectifications. Recent self-gated variants improve traditional methods in fitting flexibility by incorporating learnable content-aware fact…
Language bias in Visual Question Answering (VQA) arises when models exploit spurious statistical correlations between question templates and answers, particularly in out-of-distribution scenarios, thereby neglecting essential visual cues and compromising genuine multimodal reasoning. Despite numerou…
Nonlinearities are decisive in neural representation learning. Traditional Activation (Act) functions impose fixed inductive biases on neural networks with oriented biological intuitions. Recent methods leverage self-gated curves to compensate for the rigid traditional Act paradigms in fitting flexi…
Nonlinear Activation (Act) models which help fit the underlying mappings are critical for neural representation learning. Neuronal behaviors inspire basic Act functions, e.g., Softplus and ReLU. We instead seek improved explainable Act models by re-interpreting neural feature Act from a new philosop…
The task of ground-to-aerial image geo-localization can be achieved by matching a ground view query image to a reference database of aerial/satellite images. It is highly challenging due to the dramatic viewpoint changes and unknown orientations. In this paper, we propose a novel in-batch reweightin…