7 papers
Decoding Text Spans for Efficient and Accurate Named-Entity Recognition
Andrea Maracani, Savas Ozkan, Junyi Zhu +2
Named Entity Recognition (NER) is a key component in industrial information extraction pipelines, where systems must satisfy strict latency and throughput constraints in addition t…
Geometrically Consistent Multi-View Scene Generation from Freehand Sketches
Ahmed Bourouis, Savas Ozkan, Andrea Maracani +2
We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrically impoverished input one co…
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models
Junyi Zhu, Ruicong Yao, Taha Ceritli +6
Current network training paradigms primarily focus on either centralized or decentralized data regimes. However, in practice, data availability often exhibits a hybrid nature, wher…
Mem-MLP: Real-Time 3D Human Motion Generation from Sparse Inputs
Sinan Mutlu, Georgios F. Angelis, Savas Ozkan +3
Realistic and smooth full-body tracking is crucial for immersive AR/VR applications. Existing systems primarily track head and hands via Head Mounted Devices (HMDs) and controllers…
Multi-Task Pre-Finetuning of Lightweight Transformer Encoders for Text Classification and NER
Junyi Zhu, Savas Ozkan, Andrea Maracani +3
Deploying natural language processing (NLP) models on mobile platforms requires models that can adapt across diverse applications while remaining efficient in memory and computatio…
Efficient 3D Full-Body Motion Generation from Sparse Tracking Inputs with Temporal Windows
Georgios Fotios Angelis, Savas Ozkan, Sinan Mutlu +3
To have a seamless user experience on immersive AR/VR applications, the importance of efficient and effective Neural Network (NN) models is undeniable, since missing body parts tha…