Alicante
Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
However, the problem of provably editing a DNN to satisfy a property remains challenging.
MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction
It handles both the temporal and semantic contexts.
An Interdisciplinary Approach to Human-Centered Machine Translation
Carpuat, Marine, Asscher, Omri, Bali, Kalika, Bentivogli, Luisa, Blain, Frédéric, Bowker, Lynne, Choudhury, Monojit, Daumé, Hal III, Duh, Kevin, Gao, Ge, Grissom, Alvin II, Karpinska, Marzena, Khoong, Elaine C., Lewis, William D., Martins, André F. T., Nurminen, Mary, Oard, Douglas W., Popovic, Maja, Simard, Michel, Yvon, François
Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between system development and real-world usage, particularly for non-expert users who may struggle to assess translation reliability. This paper advocates for a human-centered approach to MT, emphasizing the alignment of system design with diverse communicative goals and contexts of use. We survey the literature in Translation Studies and Human-Computer Interaction to recontextualize MT evaluation and design to address the diverse real-world scenarios in which MT is used today.