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Found 6 papers, 0 papers with code
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval
In recent research, contrastive learning has proven to be a highly effective method for representation learning and is widely used for dense retrieval.
Fairness-Aware Domain Generalization under Covariate and Dependence Shifts
Achieving the generalization of an invariant classifier from source domains to shifted target domains while simultaneously considering model fairness is a substantial and complex challenge in machine learning.
Towards Fair Disentangled Online Learning for Changing Environments
To this end, in this paper, we propose a novel algorithm under the assumption that data collected at each time can be disentangled with two representations, an environment-invariant semantic factor and an environment-specific variation factor.
Proposing an Interactive Audit Pipeline for Visual Privacy Research
Our goal is to systematically analyze the machine learning pipeline for visual privacy and bias issues.
AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding
However, this approach constrains knowledge sharing across different attributes.
