Fei Wang

Surgical workflow image generation based on generative adversarial networks

2018

In the medical field, the labeling of surgical video data requires Expert knowledge, collecting enough numbers of marked surgical video data is difficult and time-consuming. The insufficient video data (labeled data) leads to the low …

Glyce: Glyph-vectors for Chinese Character Representations

2019 · arXiv (Cornell University)

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the use of the glyph information in those languages. However, due to the lack of rich pictographic evidence in glyphs and …

Research on Influence of Contextualization on Difficulty of Test Questions

2019 · Journal of social sciences studies

Under the background of quality teaching, teaching evaluation should pay special attention to whether students can abstract knowledge points from actual situations and solve problems by using knowledge points in contextualization questions. The contextualization of …

Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality

2023 · arXiv (Cornell University)

Improving factual consistency of abstractive summarization has been a widely studied topic. However, most of the prior works on training factuality-aware models have ignored the negative effect it has on summary quality. We propose EFACTSUM …

A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises

2023 · arXiv (Cornell University)

This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs), including their construction, utilization models, and applications across various healthcare and biomedical research domains. We thoroughly analyzed existing …

Meta Graph Learning for Long-tail Recommendation

2023

Highly skewed long-tail item distribution commonly hurts model performance on tail items in recommendation systems, especially for graph-based recommendation models. We propose a novel idea to learn relations among items as an auxiliary graph to …

Stochastic Graph Neural Network-Based Value Decomposition for Multi-Agent Reinforcement Learning in Urban Traffic Control

2023

Multi-Agent Reinforcement Learning (MARL) has reached astonishing achievements in various fields such as the traffic control of vehicles in a wireless connected environment. In MARL, how to effectively decompose a global feedback into the relative …

Design and Implementation of Automatic Music Composition System Based on Deep Learning

2024 · Journal of Electrical Systems

Recently, there has been a notable increase in interest surrounding the utilization of Deep Learning Approaches for AMCS in recent times. However, current methods often lack coherence and authenticity in the generated music. This study …

AdapTraj: A Multi-Source Domain Generalization Framework for Multi-Agent Trajectory Prediction

2024

Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects in dynamic systems, has attracted significant research attention in recent years. Despite the promising advances, existing studies all follow the assumption that …

ChatSchema: A pipeline of extracting structured information with Large Multimodal Models based on schema

2024 · arXiv (Cornell University)

Objective: This study introduces ChatSchema, an effective method for extracting and structuring information from unstructured data in medical paper reports using a combination of Large Multimodal Models (LMMs) and Optical Character Recognition (OCR) based on …

Ultra-Short-Term Power Forecasting for Distributed PV based on Multi-Source Remote Sensing Information and Adaptive Feature Extraction

2024

The lack of meteorological data for distributed photovoltaic (DPV) makes it impossible to incorporate meteorological information sources highly related to PV output into power forecasting model, which limits the further improvement of forecasting accuracy. Therefore, …

Multiensemble superradiance for distributed quantum sensing

2026 · Physical Review A

Multiensemble superradiance extends Dicke superradiance to multiple ensembles and supports dark states whose properties depend on the initial state. In the large-\(N\) limit, we derive analytical covariance matrices for these dark states, revealing inter-ensemble entanglement …

A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

State-of-the-art studies have demonstrated the superiority of joint modeling over pipeline implementation for medical named entity recognition and normalization due to the mutual benefits between the two processes. To exploit these benefits in a more …

CorefQA: Coreference Resolution as Query-based Span Prediction

2020

In this paper, we present CorefQA, an accurate and extensible approach for the coreference resolution task. We formulate the problem as a span prediction task, like in question answering: A query is generated for each …