273 citations · 336 across the 5 of their papers we have counts for
5 papers
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
Ping Yang, Junjie Wang, Ruyi Gan +6
We propose a new paradigm for zero-shot learners that is format agnostic, i.e., it is compatible with any format and applicable to a list of language tasks, such as text classifica…
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
Jiaxing Zhang, Ruyi Gan, Junjie Wang +22
Nowadays, foundation models become one of fundamental infrastructures in artificial intelligence, paving ways to the general intelligence. However, the reality presents two urgent…
Fairness-aware Model-agnostic Positive and Unlabeled Learning
Ziwei Wu, Jingrui He
With the increasing application of machine learning in high-stake decision-making problems, potential algorithmic bias towards people from certain social groups poses negative impa…
FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes
Haonan Wang, Ziwei Wu, Jingrui He
Most fair machine learning methods either highly rely on the sensitive information of the training samples or require a large modification on the target models, which hinders their…
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
Tianxin Wei, Fuli Feng, Jiawei Chen +3
The general aim of the recommender system is to provide personalized suggestions to users, which is opposed to suggesting popular items. However, the normal training paradigm, i.e.…