Projects sharing features with X Gear

Project Overview:

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

This is the github repository for the paper: Retrieval Augmented Instruction Tuning for Open NER with Large Language Models.

This is the github repository for the paper to be appeared at NAACL 2024 main conference: Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models.

Official code for ACL 2024 paper: VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large Language Models.

We provide an implementation of GCD that is compatible with the popular Transformers library!

unikg

Code and ressources for evaluating Named Entity Recognition using Few-Shot Prompting with Large Language Models

G uideline f o llowing L arge L anguage Model for I nformation E xtraction

Code and Data for arXiv paper: PolyIE: A Dataset of Information Extraction from Polymer Material Scientific Literature.

This is the code for our ACL 2024 paper Timeline-based Sentence Decomposition with In-Context Learning for Temporal Fact Extraction.

Prompting ChatGPT in MNER: Enhanced Multimodal Named Entity Recognition with Auxiliary Refined Knowledge

LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition

This repository contains code for extracting structured relational data as JSON documents from complex scientific text, with particular application to materials science. For the Llama-2 fine-tuned models and code, see the supplemetary nerre-llama repo.

If you are just looking to download the LoRA weights directly, use this url: https://figshare.com/ndownloader/files/43044994 and view the data entry on Figshare.

Code, data, and results described in the paper "Mining experimental data from materials science literature with large language models: an evaluation study", https://www.tandfonline.com/doi/full/10.1080/27660400.2024.2356506

This repository contains PyTorch implementation and pre-trained models for ASP, described in Autoregressive Structured Prediction with Language Models.

TechGPT 2.0: Technology-Oriented Generative Pretrained Transformer 2.0

The source code of paper DILUIE: Constructing Diverse Demonstrations of In-context Learning with Large Language Model for Unified Information Extraction

Exploit the power of Large Language Models (LLM) to perform Zero-Shot or Few-Shot Named Entity Recognition (NER) without the need of annotated data.

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

CHisIEC: An Information Extraction Corpus for Ancient Chinese History

This is the source code of the model RT (Retrieving and Thinking). For the full project, please check the file RTBC5CDR/3RT and RTNCBI/3RT, the implementation of GPT-NER and PromptNER is in the BC5CDR.zip and NCBI.zip. we refer to the source of code of GPT-NER and paper of GPT-NER in our project…

Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition (B 2 NER)

UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon (*Equal Contribution)

Official code for our paper "An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction" which will be published at AAAI 2024.