20 skills found
ShannonAI / CorefQAThis repo contains the code for ACL2020 paper "Coreference Resolution as Query-based Span Prediction"
neulab / SpanNERSpanNER: Named EntityRe-/Recognition as Span Prediction
hasanhuz / SpanEmoSpanEmo
vishnubashyam / DeepBrainNetConvolutional Neural Network trained for age prediction using a large (n=11,729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages, ethnicities and geographic locations around the world.
facebookresearch / ReconsiderReConsider is a re-ranking model that re-ranks the top-K (passage, answer-span) predictions of an Open-Domain QA Model like DPR (Karpukhin et al., 2020).
phusroyal / ViHOSRepository for the paper "ViHOS: Vietnamese Hate and Offensive Spans Detection" (EACL2023)
Albert-Ma / COSTASIGIR'2022, Pre-train a Discriminative Text Encoder for Dense Retrieval via Contrastive Span Prediction
nttcslab-nlp / Word AlignA Supervised Word Alignment Method based on Cross-Language Span Prediction using Multilingual BERT
thuwyh / Tweet Sentiment ExtractionPart of the 7th solution of the Kaggle Tweet Sentiment Extraction competition
nttcslab-nlp / SpanalignSpanAlign: Sentence Alignment Method based on Cross-Language Span Prediction and ILP
qiyuw / WSPAlignWSPAlign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction, to appear at ACL 2023 main conference.
urchade / Span Structured PredictionRepository for my research on span-based structured prediction for information extraction
ShubhangDesai / Tf Lstm Stock MarketLSTM-based recurrent neural network which trains RNN on 30-day span of stock data, then accepts 30-day span to make prediction for the 31st day; inspired by the following paper: https://arxiv.org/pdf/1603.07893.pdf
olonok69 / QUANTA comprehensive collection of quantitative finance research spanning classical trading strategies, deep learning models for price prediction, ensemble ML methods, and modern LLM-powered financial analysis.
ljvmiranda921 / Spacy Span AnalyzerSimple tool to analyze spans in your dataset. Implementation of Papay et al's work (EMNLP 2020) on span performance prediction
themisvaltinos / Question Answering TransformersImplementation of BERT-Based Span Entity and Relation Prediction Models for Question Answering over Wikidata
Srinath-N-R / Student Logger Gaze Tracking• This program calculates the attention span of students in online classrooms based on gaze tracking. • Input data from webcam - which after processing into text data using OpenCV & Pupil Detection - is fed into a simple neural network. • Pupil tracking was done using the Tensorflow Object Detection API. • 10 other features were also extracted with the help of simple computer vision techniques by using OpenCV & Dlib library. • Gaze tracking is successful even without requiring to initialize for the first time. • Makes 6 prediction per second. It is faster than many current models since it uses a text based simple neural network rather than a full blown CNN.
SkyTu / The Attention And Autoencoder Hybrid Learning Model• A mechanism to prolong the prediction time span of the concentration of PM2.5. • A hybrid attention mechanism taking decoder sequence into consideration, paying due attention to data in current time period. • More constraints conducted on the data with longer time span to current time.
harika1101 / Earthquake PredictionA system capable of predicting earthquake must predict about its exact location, specific magnitude range and precise time span of occurrence and probability of occurrence . Prediction has been made on the basis of mathematically calculated eight seismic indicators using the earthquake catalogue of the region.
YashNalawade / Predicting Judicial DecisionsDevelopments in Machine learning and prior work in the science of judicial prediction, the proposed system constructs a model designed to predict and mimic the behavior of the Judicial systems using NLP and Machine Learning. Proposed System intends to work upon the court data/document containing all the features including procedures, circumstances, topics, laws and relevant laws. This system can be useful, for both lawyers and judges, as an assisting tool to rapidly identify cases and extract patterns which lead to certain decisions. The goal of the system will be predicting the accuracy of violation/non-violation of articles of the constitution within a short time span. NLP here identifies each word and relates the meaning. On the other hand, machine learning here experiences each case and acquires knowledge. To the best of our knowledge, several NLP tasks have been carried out on legal texts. However, the use of text classification to predict court rulings is an under-explored area.
