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Found 7 papers, 0 papers with code
What's in the Flow? Exploiting Temporal Motion Cues for Unsupervised Generic Event Boundary Detection
This inquiry drives us to algorithmically harness motion cues for identifying generic event boundaries in videos.
Ranked #1 on
Generic Event Boundary Detection
on TAPOS
COPS: A Compact On-device Pipeline for real-time Smishing detection
Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping.
TrICy: Trigger-guided Data-to-text Generation with Intent aware Attention-Copy
Data-to-text (D2T) generation is a crucial task in many natural language understanding (NLU) applications and forms the foundation of task-oriented dialog systems.
Ranked #3 on
Data-to-Text Generation
on E2E NLG Challenge
PrivPAS: A real time Privacy-Preserving AI System and applied ethics
This motivates us to work towards a solution to generate privacy-conscious cues for raising awareness in smartphone users of any sensitivity in their viewfinder content.
edATLAS: An Efficient Disambiguation Algorithm for Texting in Languages with Abugida Scripts
To this end, we propose a disambiguation algorithm and showcase its usefulness in two novel mutually non-exclusive input methods for languages natively using the abugida writing system: (a) disambiguation of ambiguous input for abugida scripts, and (b) disambiguation of word variants in romanized scripts.
EmpLite: A Lightweight Sequence Labeling Model for Emphasis Selection of Short Texts
To the best of our knowledge, this work presents the first lightweight deep learning approach for smartphone deployment of emphasis selection.
LiteMuL: A Lightweight On-Device Sequence Tagger using Multi-task Learning
The proposed LiteMuL not only outperforms the current state of the art results but also surpasses the results of our proposed on-device task-specific models, with accuracy gains of up to 11% and model-size reduction by 50%-56%.
