Projects sharing features with Event Extraction As Question Generation And Answering

This project is a transformer-based language model and autoregressive text generator designed to predict the next token in a sequence to produce human-like prose and synthetic text. It functions as a large language model that utilizes a transformer architecture to learn linguistic patterns from large datasets for unsupervised multitask learning. The repository provides a distribution of pre-trained weights, enabling natural language processing tasks without requiring additional training. This allows the model to perform zero-shot task generalization by applying learned patterns to new tasks.

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents within photorealistic indoor and outdoor environments. It serves as a simulator for AI and robotics, providing a system for generating synthetic data and simulating physical interactions. The project is distinguished by a native C++ core that enables high-throughput simulation and a rendering pipeline using physically based rendering and baked global illumination. It features a navigation system based on pre-computed navigation meshes to ensure collision-free traversal and a rigi

This project is a collection of deep learning courseware and instructional materials. It provides a structured curriculum and practical demonstrations covering the fundamentals of neural network architectures and artificial intelligence. The materials include specialized tutorials and guides on generative adversarial networks for synthetic data generation, as well as reinforcement learning resources focused on decision-making and motion planning for autonomous robotics. The content covers broad capability areas including computer vision development, the implementation of feed-forward and con

This project is a collection of PyTorch learning resources and educational guides designed to teach the construction and training of neural networks. It serves as a comprehensive deep learning tutorial covering various model architectures and practical implementation strategies. The resources provide specific guidance on implementing computer vision tasks, such as image classification and synthetic imagery generation, as well as reinforcement learning agents using value networks and experience replay. It also covers sequential data modeling through recurrent networks and generative modeling u

A concept and obvious expression pattern collection of Chinese compound event extraction which then be evolved into ComplexEventGraph，本项目提出了中文复合事件的概念与显式模式，包括条件事件、因果事件、顺承事件、反转事件等事件抽取，并形成事理图谱。

An exploration for Eventline (important news Rank organized by pulic time)，针对某一事件话题下的新闻报道集合，通过使用docrank算法，对新闻报道进行重要性识别，并通过新闻报道时间挑选出时间线上重要新闻。

An implementation for Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction - Please contact Yaojie Lu (@luyaojie) for questions and suggestions.

Source code for Findings of ACL 2024 paper: Beyond Single-Event Extraction: Towards Efficient Document-Level Multi-Event Argument Extraction.

This is the implementation of filter-then-rerank pipeline in Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!. EMNLP'2023 (Findings).

This is the implementation of the paper Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction. ACL'2022.

Pytorch Solution of Event Extraction Task using BERT on ACE 2005 corpus

Code repository for paper "KeyEE: Enhancing Low-resource Generative Event Extraction with Auxiliary Keyword Sub-Prompt".

Code for our ACL-2023 paper AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Model

Code for our NAACL-2022 paper DEGREE: A Data-Efficient Generation-Based Event Extraction Model.

This repository is the official implementation of MLBiNet: A Cross-Sentence Collective Event Detection Network.

A list of NLP resources focused on event extraction task

Source code and data for ACL 2023 main conference paper DICE: Data-Efficient Clinical Event Extraction with Generative Models.

Updates | Datasets | Models | Environment | Running | Results | Website | Paper

This repository contains the PyTorch implementation for the models and experiments in Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

This repository contains the code for our paper:

This is a meta-model distilled from ChatGPT-3.5-turbo for information extraction. This is an intermediate checkpoint that can be well-transferred to all kinds of downstream information extraction tasks.

The pre-trained corpus of ClarET is the same as that of EventBERT and can be found in CORPUS.

Code for "Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study" (EACL 2024).

Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21'

This repo contains the code and datasets for paper "ProgGen: Generating Named Entity Recognition Datasets Step-by-step with Self-Reflexive Large Language Models".