推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Remove problematic gender bias from word embeddings.

Counterfactual Samples Synthesizing for Robust VQA

[ICCV 2023] PyTorch implementation of RandBox

[EMNLP 2023] Official Code of "JointMatch: A Unified Approach for Diverse and Collaborative Pseudo-Labeling to Semi-Supervised Text Classification"

Debiasing both contextual and context free embeddings and developing a downstream metric for bias measurement

[EMNLP 2023] Official Code of "DeCrisisMB: Debiased Semi-Supervised Learning for Crisis Tweet Classification via Memory Bank"

Course 5 from deeplearning.ai

Extension of bias-bench for select Sentence Transformers* models

Identifying gender bias in film reviews through three distinct Natural Language Processing models