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Found 9 papers, 4 papers with code
ProDial – An Annotated Proactive Dialogue Act Corpus for Conversational Assistants using Crowdsourcing
For creating a sound interactive personalization, we have developed an empathy-augmented dialogue strategy.
Personalized Collaborative Fine-Tuning for On-Device Large Language Models
We explore on-device self-supervised collaborative fine-tuning of large language models with limited local data availability.
Improving Proactive Dialog Agents Using Socially-Aware Reinforcement Learning
The next step for intelligent dialog agents is to escape their role as silent bystanders and become proactive.
Federated Stain Normalization for Computational Pathology
As a solution, we propose BottleGAN, a generative model that can computationally align the staining styles of many laboratories and can be trained in a privacy-preserving manner to foster federated learning in computational pathology.
Scalable 3D Semantic Segmentation for Gun Detection in CT Scans
With the increased availability of 3D data, the need for solutions processing those also increased rapidly.
NeuralQAAD: An Efficient Differentiable Framework for High Resolution Point Cloud Compression
As evaluating the EMD on high resolution point clouds is intractable, we propose a divide-and-conquer approach based on k-d trees, the EM-kD, as a scaleable and fast but still reliable upper bound for the EMD.
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation
Most deep neural networks are considered to be black boxes, meaning their output is hard to interpret.
Super-Selfish: Self-Supervised Learning on Images with PyTorch
Super-Selfish is an easy to use PyTorch framework for image-based self-supervised learning.
Utilisation de Repr\'esentations Distribu\'ees de Relations pour la D\'esambigu\"\isation d'Entit\'es Nomm\'ees (Exploiting Relation Embeddings to Improve Entity Linking )
L{'}identification des entit{\'e}s nomm{\'e}es dans un texte est une {\'e}tape fondamentale pour de nombreuses t{\^a}ches d{'}extraction d{'}information.
