Search Results for author:
Found 10 papers, 6 papers with code
Deep Learning based Visually Rich Document Content Understanding: A Survey
In response to the growing demands and rapid developments in Visually Rich Document Understanding (VRDU), this paper provides a comprehensive review of deep learning-based VRDU frameworks.
Selecting Experimental Sites for External Validity
Policy decisions often depend on evidence generated elsewhere.
3MVRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding
This paper presents a groundbreaking multimodal, multi-task, multi-teacher joint-grained knowledge distillation model for visually-rich form document understanding.
A Survey of Large Language Models in Finance (FinLLMs)
This survey provides a comprehensive overview of FinLLMs, including their history, techniques, performance, and opportunities and challenges.
StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series
There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited.
Emotion Classification
Multivariate Time Series Forecasting
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K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment
Online hate speech detection has become an important issue due to the growth of online content, but resources in languages other than English are extremely limited.
FedNLP: An interpretable NLP System to Decode Federal Reserve Communications
The Federal Reserve System (the Fed) plays a significant role in affecting monetary policy and financial conditions worldwide.
CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection
Accompanying the dataset is a thorough in-game toxicity analysis, which provides comprehensive understanding of context at utterance, token, and dual levels.
Choosing Transfer Languages for Cross-Lingual Learning
Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.
Towards a General-Purpose Linguistic Annotation Backend
In this extended abstract, we describe the beginnings of a new project that will attempt to ease this language documentation process through the use of natural language processing (NLP) technology.
