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Found 16 papers, 2 papers with code
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization
We introduce a deep reinforcement learning approach to topic-focused abstractive summarization, trained on rewards with a novel negative example baseline.
MGIC: A Multi-Label Gradient Inversion Attack based on Canny Edge Detection on Federated Learning
As a new distributed computing framework that can protect data privacy, federated learning (FL) has attracted more and more attention in recent years.
RAF-GI: Towards Robust, Accurate and Fast-Convergent Gradient Inversion Attack in Federated Learning
Yet, FL users are susceptible to the gradient inversion (GI) attack which can reconstruct ground-truth training data such as images based on model gradients.
1D-Touch: NLP-Assisted Coarse Text Selection via a Semi-Direct Gesture
We introduce 1D-Touch, a novel text selection method that complements the carets-based sub-word selection by facilitating the selection of semantic units of words and above.
ONNXExplainer: an ONNX Based Generic Framework to Explain Neural Networks Using Shapley Values
SHAP package is a leading implementation of Shapley values to explain neural networks implemented in TensorFlow or PyTorch but lacks cross-platform support, one-shot deployment and is highly inefficient.
On Conditional and Compositional Language Model Differentiable Prompting
Prompts have been shown to be an effective method to adapt a frozen Pretrained Language Model (PLM) to perform well on downstream tasks.
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation
Our controlled experiments show that the keys to improving downstream performance on disease classification are (1) using patient metadata to appropriately create positive pairs from different images with the same underlying pathologies, and (2) maximizing the number of different images used in query pairing.
Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning
Navigating fluently around pedestrians is a necessary capability for mobile robots deployed in human environments, such as buildings and homes.
DAWSON: A Domain Adaptive Few Shot Generation Framework
Based on DAWSON, We also propose MUSIC MATINEE, which is the first few-shot music generation model.
Quantifying the Security of Recognition Passwords: Gestures and Signatures
We use a partial guessing metric, which demonstrates how many guesses an attacker needs to crack a percentage of the entire space, to compare the security of the distributions for gestures, signatures, and Android unlock patterns.
Cryptography and Security
A Model for Medical Diagnosis Based on Plantar Pressure
Here, we propose a model using convolutional neural network based on plantar pressure for medical diagnosis.
