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InSaAF: Incorporating Safety through Accuracy and Fairness | Are LLMs ready for the Indian Legal Domain?
Task performance and fairness scores of LLaMA and LLaMA--2 models indicate that the proposed $LSS_{\beta}$ metric can effectively determine the readiness of a model for safe usage in the legal sector.
LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks
To overcome these limitations, we propose novel line conversation graph convolutional network (LineConGCN) and graph attention (LineConGAT) models for ERC analysis.
Are Models Trained on Indian Legal Data Fair?
We highlight the propagation of learnt algorithmic biases in the bail prediction task for models trained on Hindi legal documents.
Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes
Such unstructured clinical notes recorded by medical personnel can also be a potential source of rich patient-specific information which can be leveraged to build CDSSs, even for hospitals in developing countries.
Coherence-based Modeling of Clinical Concepts Inferred from Heterogeneous Clinical Notes for ICU Patient Risk Stratification
In hospitals, critical care patients are often susceptible to various complications that adversely affect their morbidity and mortality.
