njcx-ai

Awesome-Multimodal-Large-Language-Models

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

GPT-4-LLM

Instruction Tuning with GPT-4

DeepKE

[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction

DeepIE

DeepIE: Deep Learning for Information Extraction

KnowLM

An Open-sourced Knowledgable Large Language Model Framework.

acad-homepage.github.io

AcadHomepage: A Modern and Responsive Academic Personal Homepage

Awesome-Knowledge-Graph-Reasoning

AKGR: Awesome Knowledge Graph Reasoning is a collection of knowledge graph reasoning works, including papers, codes and datasets

ImageNet21K

Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper

PromptKG

PromptKG Family: a Gallery of Prompt Learning & KG-related research works, toolkits, and paper-list.

awesome-hallucination-detection

List of papers on hallucination detection in LLMs.

reflexion-draft

Reflexion: an autonomous agent with dynamic memory and self-reflection

EasyInstruct

[ACL 2024] An Easy-to-use Instruction Processing Framework for LLMs.

KnowPrompt

[WWW 2022] KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction

MKGformer

[SIGIR 2022] Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

PTR

Prompt Tuning with Rules

DART

[ICLR 2022] Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

DocuNet

[IJCAI 2021] Document-level Relation Extraction as Semantic Segmentation

HVPNeT

[NAACL 2022 Findings] Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction

KCL

Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]

MELBench

Multimodal entity linking (MEL) aims to utilize multimodal information to map mentions to corresponding entities defined in knowledge bases. We release three MEL datasets: Weibo-MEL, Wikidata-MEL and Richpedia-MEL, containing 25,602, 18,880 and 17,806 samples from social media, encyclopedia and multimodal knowledge graphs respectively. A MEL dataset construction approach is proposed, including five stages: multimodal information extraction, mention extraction, entity extraction, triple construction and dataset construction. Experiment results demonstrate the usability of the datasets and the distinguishability between baseline models.

FactCHD

[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection

KNN-KG

[NLPCC 2023] Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings with Language Models

EasyDetect

An Easy-to-use Hallucination Detection Framework for LLMs.

RJU_Ant_QA

The RJUA-QA (RenJi hospital department of Urology and Antgroup collaborative Question and Answer dataset) is an innovative medical urology specialty QA inference dataset.

LREBench

[EMNLP 2022 Findings] Towards Realistic Low-resource Relation Extraction: A Benchmark with Empirical Baseline Study

DiagnoseRE

[CCKS 2021] On Robustness and Bias Analysis of BERT-based Relation Extraction

KEFDA

CoLL

A continual learning framework for natural language processing.

awesome-multimodal-knowledge-graph

A curated list of AWESOME papers, datasets and tutorials within Multimodal Knowledge Graph.

DocuNet

Source code and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".