3 papers
cs.CL2023
Span-Selective Linear Attention Transformers for Effective and Robust Schema-Guided Dialogue State Tracking
Björn Bebensee, Haejun Lee
In schema-guided dialogue state tracking models estimate the current state of a conversation using natural language descriptions of the service schema for generalization to unseen…
cs.CV2020
Co-attentional Transformers for Story-Based Video Understanding
Björn Bebensee, Byoung-Tak Zhang
Inspired by recent trends in vision and language learning, we explore applications of attention mechanisms for visio-lingual fusion within an application to story-based video under…
cs.CR2019
Local Differential Privacy: a tutorial
Björn Bebensee
In the past decade analysis of big data has proven to be extremely valuable in many contexts. Local Differential Privacy (LDP) is a state-of-the-art approach which allows statistic…