Stars
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP'24)
Generative Representational Instruction Tuning
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs (ACL 2024)
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
A curated list for Efficient Large Language Models
A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey" (TKDE)
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Patton: Language Model Pretraining on Text-rich Networks (ACL 2023 main oral)
High-performance In-browser LLM Inference Engine
[ICLR 2024] Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters
Reading list of Instruction-tuning. A trend starts from Natrural-Instruction (ACL 2022), FLAN (ICLR 2022) and T0 (ICLR 2022).
The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study (WWW'23)
NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')
Papers about developing deep Graph Neural Networks (GNNs)
MATCH: Metadata-Aware Text Classification in A Large Hierarchy (WWW'21)
Minimally Supervised Categorization of Text with Metadata (SIGIR'20)
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)
Repository for benchmarking graph neural networks (JMLR 2023)
ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks
Strategies for Pre-training Graph Neural Networks
The source code used for self-supervised taxonomy expansion method TaxoExpan, published in WWW 2020
Unsupervised clustering with (Gaussian mixture) VAEs
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
On the Variance of the Adaptive Learning Rate and Beyond
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories (ICDM'19)
Source code and dataset for KDD 2019 paper "OAG: Toward Linking Large-scale Heterogeneous Entity Graphs"