7 papers
Causally Fair Node Classification on Non-IID Graph Data
Yucong Dai, Lu Zhang, Yaowei Hu +2
Fair machine learning seeks to identify and mitigate biases in predictions against unfavorable populations characterized by demographic attributes, such as race and gender. Recent…
ClusterRAG: Cluster-Based Collaborative Filtering for Personalized Retrieval-Augmented Generation
Gibson Nkhata, Uttamasha Anjally Oyshi, Quan Mai +1
Personalized Retrieval-Augmented Generation (RAG) relies on accurately selecting user-relevant documents. In practice, existing RAG approaches often suffer from high retrieval cost…
Fair Learning for Bias Mitigation and Quality Optimization in Paper Recommendation
Uttamasha Anjally Oyshi, Susan Gauch
Despite frequent double-blind review, demographic biases of authors still disadvantage the underrepresented groups. We present Fair-PaperRec, a MultiLayer Perceptron (MLP)-based mo…
Causal Analysis of Author Demographics in Academic Peer Review
Uttamasha Anjally Oyshi, Gibson Nkhata, Susan Gauch
Academic meritocracy is jeopardized by systematic imbalances; for example, whereas Black and Hispanic individuals constitute over 30% of the U.S. population, they represent fewer t…
Sarcasm Detection as a Catalyst: Improving Stance Detection with Cross-Target Capabilities
Gibson Nkhata Shi Yin Hong, Susan Gauch
Stance Detection (SD) has become a critical area of interest due to its applications in various contexts leading to increased research within NLP. Yet the subtlety and complexity o…
Intermediate-Task Transfer Learning: Leveraging Sarcasm Detection for Stance Detection
Gibson Nkhata, Susan Gauch
Stance Detection (SD) on social media has emerged as a prominent area of interest with implications for social business and political applications thereby garnering escalating rese…