Awesome-LLM: a curated list of Large Language Model

[NeurIPS 2024] Official Code for the Paper "Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning"

😎 up-to-date & curated list of awesome Attacks on Large-Vision-Language-Models papers, methods & resources.

WWW 2024: New Frontiers of Knowledge Graph Reasoning: Recent Advances and Future Trends

A curated collection of research papers exploring the utilization of LLMs for graph-related tasks.

A collection of AWESOME things about Graph-Related LLMs.

Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models

Another LaTeX Academic CV Template

Mutual Information Neural Estimation in Pytorch

Graph Few-Shot Class-Incremental Learning via Prototype Representation

Code for One-shot Relational Learning for Knowledge Graphs (EMNLP18)

Pytorch Implementation of WSDM 2022 -- Graph Few-shot Class-incremental Learning

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

An NSF proposal template in LaTeX

A curated list of papers, code and resources pertaining to weak-shot classification, detection, and segmentation.

Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs" (KDD 2021).

Github Pages template based upon HTML and Markdown for personal, portfolio-based websites.

Academic CV of Christopher Morris.

LaTeX Template for (Academic) CVs Following Dr. Karen's Rules

Code and dataset for paper "Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts" published in KDD'2019.

Neural Graph Collaborative Filtering, SIGIR2019

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

List of AI Residency Programs

Implementation of SurfCon model for Synonym Discovery on Privacy-Aware Clinical Data

Latex CV template built with Font Awesome.

Representation learning on large graphs using stochastic graph convolutions.

This is a dataset for fake news detection research