  Modern information querying systems are progressively incorporating
multimodal inputs like vision and audio. However, the integration of gaze -- a
modality deeply linked to user intent and increasingly accessible via
gaze-tracking wearables -- remains underexplored. This paper introduces a novel
gaze-facilitated information querying paradigm, named G-VOILA, which synergizes
users' gaze, visual field, and voice-based natural language queries to
facilitate a more intuitive querying process. In a user-enactment study
involving 21 participants in 3 daily scenarios (p = 21, scene = 3), we revealed
the ambiguity in users' query language and a gaze-voice coordination pattern in
users' natural query behaviors with G-VOILA. Based on the quantitative and
qualitative findings, we developed a design framework for the G-VOILA paradigm,
which effectively integrates the gaze data with the in-situ querying context.
Then we implemented a G-VOILA proof-of-concept using cutting-edge deep learning
techniques. A follow-up user study (p = 16, scene = 2) demonstrates its
effectiveness by achieving both higher objective score and subjective score,
compared to a baseline without gaze data. We further conducted interviews and
provided insights for future gaze-facilitated information querying systems.
