Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)

Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

A python library for social event detection

A list of NLP resources focused on event extraction task

Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?

A comprehensive, unified and modular event extraction toolkit.

GolfDB is a video database for Golf Swing Sequencing, which involves detecting 8 golf swing events in trimmed golf swing videos. This repo demos the baseline model, SwingNet.

Applying Deep Learning Approaches to Volleyball Data

Evaluating ChatGPT’s Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

An Evaluation of ChatGPT on Information Extraction task, including Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE) and Aspect-based Sentiment Analysis (ABSA).

[ACL 2021-Findings] Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading."

A python package for processing eye movement data

Source code and dataset for NAACL 2019 paper "Adversarial Training for Weakly Supervised Event Detection".

The source code for the real-time hand gesture recognition algorithm based on Temporal Muscle Activation maps of multi-channel surface electromyography (sEMG) signals (ICASSP 2021)

Segmentation based event detection from Tweets. Published at NAACL SRW 2019

Papers from top conferences and journals for event extraction in recent years

RawHash can accurately and efficiently map raw nanopore signals to reference genomes of varying sizes (e.g., from viral to a human genomes) in real-time without basecalling. Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440).

A standardized, fair, and reproducible benchmark for evaluating event extraction approaches

Event Detection and Domain Adaptation with Convolutional Neural Networks

🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.