mouxingyang

Awesome-RAG

Awesome-LLM-RAG

Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models

PC2-NoiseofWeb

Noise of Web (NoW) is a challenging noisy correspondence learning (NCL) benchmark containing 100K image-text pairs for robust image-text matching/retrieval models.

awesome-multi-omics

List of software packages for multi-omics analysis

OPERA

[CVPR 2024 Highlight] OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

VCD

[CVPR 2024 Highlight] Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

less-is-more

Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective (ACL 2024)

protein-bert-pytorch

Implementation of ProteinBERT in Pytorch

scmFormer

protein_bert

Awesome-MLLM-Hallucination

📖 A curated list of resources dedicated to hallucination of multimodal large language models (MLLM).

awesome-foundation-model-single-cell-papers

scGPT

Awesome-Multimodal-Large-Language-Models

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

Awesome-Noisy-Correspondence

This is a summary of research on noisy correspondence. There may be omissions. If anything is missing please get in touch with us. Our emails: linyijie.gm@gmail.com yangmouxing@gmail.com qinyang.gm@gmail.com

scJoint

awesome-deep-learning-single-cell-papers

scBERT

scCLIP

Awesome-Healthcare-Foundation-Models

2024-ICLR-READ

Pytorch implementation of "Test-time Adaption against Multi-modal Reliability Bias".

Awesome-Noisy-Correspondence

This is a summary of research on noisy correspondence. There may be omissions. If anything is missing please get in touch with us. Our emails: linyijie.gm@gmail.com yangmouxing@gmail.com qinyang.gm@gmail.com

2024-IJCV-LCNL

cav-mae

Code and Pretrained Models for ICLR 2023 Paper "Contrastive Audio-Visual Masked Autoencoder".

VideoLanguageModelRobustness

A large scale robustness analysis for video and text, multimodal models on the YouCook2 and MSRVTT datasets.

MM_Robustness

[DMLR 2024] Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift

TCL

code for TCL: Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022

CLIP_benchmark

CLIP-like model evaluation

missing_aware_prompts

Multimodal Prompting with Missing Modalities for Visual Recognition, CVPR'23

gpt-4v-distribution-shift

Code for "How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation"