no code implementations • 16 Feb 2024 • Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje, Ishan Kavathekar, Bhaskara Hanuma Vedula, Gokul S Krishnan, Shreya Goyal, Anmol Goel, Balaraman Ravindran, Ponnurangam Kumaraguru
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.
no code implementations • 4 Dec 2023 • Gokul S Krishnan, Sarala Padi, Craig S. Greenberg, Balaraman Ravindran, Dinesh Manoch, Ram D. Sriram
To overcome these limitations, we propose novel line conversation graph convolutional network (LineConGCN) and graph attention (LineConGAT) models for ERC analysis.
no code implementations • 13 Mar 2023 • Sahil Girhepuje, Anmol Goel, Gokul S Krishnan, Shreya Goyal, Satyendra Pandey, Ponnurangam Kumaraguru, Balaraman Ravindran
We highlight the propagation of learnt algorithmic biases in the bail prediction task for models trained on Hindi legal documents.
no code implementations • 26 Nov 2019 • Gokul S Krishnan, Sowmya Kamath S
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.
no code implementations • CONLL 2019 • Tushaar Gangavarapu, Gokul S Krishnan, Sowmya Kamath S
In hospitals, critical care patients are often susceptible to various complications that adversely affect their morbidity and mortality.