less-and-less-bugs

Trust_TELLER

The official implementation of our paper "TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detection".

unify

HKEmodel

Official implementation of Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge Enhancement.

LogicMD

The offical code implementation of paper "Interpretable Multimodal Misinformation Detection with Logic Reasoning", accepted by Finding of ACL 23.

RDCM

Formal implementation of Robust Domain Misinformation Detection via Multi-modal Feature Alignment

Awesome-Sentence-Embedding

A curated list of research papers in Sentence Reprsentation Learning and a sts leaderboard of sentence embeddings.

NExT-GPT

Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model

awesome-phd-advice

Collection of advice for prospective and current PhD students

openai-cookbook

Examples and guides for using the OpenAI API

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

Awesome-Domain-Generalization

Awesome things about domain generalization, including papers, code, etc.

rust_circuit_public

mmdetection

OpenMMLab Detection Toolbox and Benchmark

tul

transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

HowToCook

程序员在家做饭方法指南。Programmer's guide about how to cook at home (Chinese only).

vision_transformer

pytorch_memlab

debug with OOM problem for pytorch

mmdemo-dockerized

A set of services for monitoring of multiple social media platforms based on Docker.

adamwr

Implements https://arxiv.org/abs/1711.05101 AdamW optimizer, cosine learning rate scheduler and "Cyclical Learning Rates for Training Neural Networks" https://arxiv.org/abs/1506.01186 for PyTorch framework

HGNN

Hypergraph Neural Networks (AAAI 2019)

first-stbank

Feasible target propagation code for the paper "Deep Learning as a Mixed Convex-Combinatorial Optimization Problem" by Friesen & Domingos (2018).