Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

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Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

We demonstrate a nonlinear plasmonic metasurface that exhibits strongly asymmetric second-harmonic generation: nonlinear scattering is efficient upon excitation in one direction, and it is substantially suppressed when the excitation direction is reversed, ...

The SALUTE project aims at evaluating performance of electroacoustic metasurface, employing a surface array of controlled electroacoustic actuators, for smart acoustic lining under grazing turbulent flow to be used in UHBR Technologies Engines. Theoretical ...

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

Introduced to enable a wider use of Earth Observation images using natural language, Remote Sensing Visual Question Answering (RSVQA) remains a challenging task, in particular for questions related to counting. To address this specific challenge, we propos ...

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

Technology supporting meditation is a multimillion-dollar market that continues to grow. There is also strong academic interest to understand and improve the impact technology can have for the user experience of practitioners. However, little work investig ...

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

Chattez avec Graph Search

Modeling Structured Data in Attention-based Models

Text Representation Learning for Low Cost Natural Language Understanding

Demonstration of a Plasmonic Nonlinear Pseudodiode

Smart acoustic lining for UHBR technologies engine: from the design of an electroacoustic metasurface to experimental characterization under flow

Backpropagation-free training of deep physical neural networks

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Transformer Models for Vision

Adapting Haptic Feedback for Guided Meditation

Improving Generalization of Pretrained Language Models