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Found 13 papers, 5 papers with code
Measuring Recency Bias In Sequential Recommendation Systems
Recency bias in a sequential recommendation system refers to the overly high emphasis placed on recent items within a user session.
Safe-Embed: Unveiling the Safety-Critical Knowledge of Sentence Encoders
This paper investigates the potential of sentence encoders to distinguish safe from unsafe prompts, and the ability to classify various unsafe prompts according to a safety taxonomy.
Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-rays
The model is developed using a step-by-step approach, starting with being pretrained on natural images and texts, followed by being trained using longitudinal chest X-ray data.
MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection
It is designed to incorporate a novel memory module that can learn the degree to which each memory item should be updated in response to the input data.
Named Entity Normalization Model Using Edge Weight Updating Neural Network: Assimilation Between Knowledge-Driven Graph and Data-Driven Graph
More precise named entity normalization in text mining will benefit other subsequent text analytic applications.
Automatic Construction of Context-Aware Sentiment Lexicon in the Financial Domain Using Direction-Dependent Words
Increasing attention has been drawn to the sentiment analysis of financial documents.
Domain-slot Relationship Modeling using a Pre-trained Language Encoder for Multi-Domain Dialogue State Tracking
We propose a model for multi-domain dialogue state tracking that effectively models the relationship among domain-slot pairs using a pre-trained language encoder.
SARN: Relational Reasoning through Sequential Attention
This paper proposes an attention module augmented relational network called SARN(Sequential Attention Relational Network) that can carry out relational reasoning by extracting reference objects and making efficient pairing between objects.
CRAM: Clued Recurrent Attention Model
To overcome the poor scalability of convolutional neural network, recurrent attention model(RAM) selectively choose what and where to look on the image.
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning
To solve the text-based question and answering task that requires relational reasoning, it is necessary to memorize a large amount of information and find out the question relevant information from the memory.
Ranked #4 on
Question Answering
on bAbi
(Mean Error Rate metric)
Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things
In this paper, we propose Squeezed Convolutional Variational AutoEncoder (SCVAE) for anomaly detection in time series data for Edge Computing in Industrial Internet of Things (IIoT).
Distance-based Self-Attention Network for Natural Language Inference
Motivated by the Transformer, Directional Self Attention Network (Shen et al., 2017), a fully attention-based sentence encoder, was proposed.
Ranked #54 on
Natural Language Inference
on SNLI
Variational Autoencoder based Anomaly Detection using Reconstruction Probability
We propose an anomaly detection method using the reconstruction probability from the variational autoencoder.
