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07/28/2023
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Graph Neural Networks (GNNs) have proven to be effective in processing a...
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07/16/2023
Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank Regression
Time-to-event analysis, also known as survival analysis, aims to predict...
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07/10/2023
KU-DMIS-MSRA at RadSum23: Pre-trained Vision-Language Model for Radiology Report Summarization
In this paper, we introduce CheXOFA, a new pre-trained vision-language m...
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04/21/2023
KitchenScale: Learning to predict ingredient quantities from recipe contexts
Determining proper quantities for ingredients is an essential part of co...
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04/11/2023
ELVIS: Empowering Locality of Vision Language Pre-training with Intra-modal Similarity
Deep learning has shown great potential in assisting radiologists in rea...
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02/03/2023
LIQUID: A Framework for List Question Answering Dataset Generation
Question answering (QA) models often rely on large-scale training datase...
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12/01/2022
Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework
In order to assist the drug discovery/development process, pharmaceutica...
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10/24/2022
Enhancing Label Consistency on Document-level Named Entity Recognition
Named entity recognition (NER) is a fundamental part of extracting infor...
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10/14/2022
Automatic Creation of Named Entity Recognition Datasets by Querying Phrase Representations
Most weakly supervised named entity recognition (NER) models rely on dom...
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10/14/2022
RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer
We propose a computational approach for recipe ideation, a downstream ta...
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06/29/2022
Deformable Graph Transformer
Transformer-based models have been widely used and achieved state-of-the...
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06/09/2022
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
Graph Neural Networks (GNNs) have been widely applied to various fields ...
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05/25/2022
Refining Query Representations for Dense Retrieval at Test Time
Dense retrieval uses a contrastive learning framework to learn dense rep...
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05/25/2022
Towards More Realistic Generation of Information-Seeking Conversations
In this paper, we introduce a novel framework SimSeek (simulating inform...
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05/24/2022
Lack of Fluency is Hurting Your Translation Model
Many machine translation models are trained on bilingual corpus, which c...
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01/06/2022
BERN2: an advanced neural biomedical named entity recognition and normalization tool
In biomedical natural language processing, named entity recognition (NER...
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12/16/2021
Simple Questions Generate Named Entity Recognition Datasets
Named entity recognition (NER) is a task of extracting named entities of...
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11/20/2021
Improving Tagging Consistency and Entity Coverage for Chemical Identification in Full-text Articles
This paper is a technical report on our system submitted to the chemical...
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09/15/2021
Can Language Models be Biomedical Knowledge Bases?
Pre-trained language models (LMs) have become ubiquitous in solving vari...
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07/05/2021
FaVIQ: FAct Verification from Information-seeking Questions
Despite significant interest in developing general purpose fact checking...
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06/22/2021
Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering
One of the main challenges in conversational question answering (CQA) is...
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06/11/2021
Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs
Graph Neural Networks (GNNs) have been widely applied to various fields ...
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04/28/2021
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Human-Object Interaction (HOI) detection is a task of identifying "a set...
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04/15/2021
Sequence Tagging for Biomedical Extractive Question Answering
Current studies in extractive question answering (EQA) have modeled sing...
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04/15/2021
Consistency Training with Virtual Adversarial Discrete Perturbation
We propose an effective consistency training framework that enforces a t...
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04/15/2021
Regularizing Models via Pointwise Mutual Information for Named Entity Recognition
In Named Entity Recognition (NER), pre-trained language models have been...
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01/15/2021
"Killing Me" Is Not a Spoiler: Spoiler Detection Model using Graph Neural Networks with Dependency Relation-Aware Attention Mechanism
Several machine learning-based spoiler detection models have been propos...
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01/01/2021
How Do Your Biomedical Named Entity Models Generalize to Novel Entities?
The number of biomedical literature on new biomedical concepts is rapidl...
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12/23/2020
Learning Dense Representations of Phrases at Scale
Open-domain question answering can be reformulated as a phrase retrieval...
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10/20/2020
Robust Neural Networks inspired by Strong Stability Preserving Runge-Kutta methods
Deep neural networks have achieved state-of-the-art performance in a var...
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09/26/2020
Can pandemics transform scientific novelty? Evidence from COVID-19
Scientific novelty is important during the pandemic due to its critical ...
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07/10/2020
MAPS: Multi-agent Reinforcement Learning-based Portfolio Management System
Generating an investment strategy using advanced deep learning methods i...
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07/01/2020
Transferability of Natural Language Inference to Biomedical Question Answering
Biomedical question answering (QA) is a challenging problem due to the s...
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06/29/2020
Answering Questions on COVID-19 in Real-Time
The recent outbreak of the novel coronavirus is wreaking havoc on the wo...
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05/08/2020
Building a PubMed knowledge graph
PubMed is an essential resource for the medical domain, but useful conce...
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05/01/2020
Biomedical Entity Representations with Synonym Marginalization
Biomedical named entities often play important roles in many biomedical ...
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04/30/2020
Look at the First Sentence: Position Bias in Question Answering
Many extractive question answering models are trained to predict start a...
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04/29/2020
Adversarial Subword Regularization for Robust Neural Machine Translation
Exposing diverse subword segmentations to neural machine translation (NM...
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04/11/2020
Exploring The Spatial Reasoning Ability of Neural Models in Human IQ Tests
Although neural models have performed impressively well on various tasks...
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02/18/2020
Learning by Semantic Similarity Makes Abstractive Summarization Better
One of the obstacles of abstractive summarization is the presence of var...
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11/07/2019
Contextualized Sparse Representation with Rectified N-Gram Attention for Open-Domain Question Answering
A sparse representation is known to be an effective means to encode prec...
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09/18/2019
Pre-trained Language Model for Biomedical Question Answering
The recent success of question answering systems is largely attributed t...
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08/07/2019
HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
Many researchers both in academia and industry have long been interested...
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05/27/2019
SAIN: Self-Attentive Integration Network for Recommendation
With the growing importance of personalized recommendation, numerous rec...
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05/16/2019
KitcheNette: Predicting and Recommending Food Ingredient Pairings using Siamese Neural Networks
As a vast number of ingredients exist in the culinary world, there are c...
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04/17/2019
Self-Attention Graph Pooling
Advanced methods of applying deep learning to structured data such as gr...
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03/25/2019
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network
Most companies utilize demographic information to develop their strategy...
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02/28/2019
Global Stock Market Prediction Based on Stock Chart Images Using Deep Q-Network
We applied Deep Q-Network with a Convolutional Neural Network function a...
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01/25/2019
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Biomedical text mining is becoming increasingly important as the number ...
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01/25/2019
